JPH11112352A - Encoding device and decoding device - Google Patents

Abstract

(57) [Summary] When the information amount of an input image is large, distortion due to quantization increases, and block distortion occurs. A pre-filter means for restricting a transmission band of an input signal from an input means, and a pre-filter means.
And orthogonal transform encoding means 26 for quantizing and encoding the output of 5 in the orthogonal transform, and the pre-filter means 25 comprises:
When the quantization width used in the past encoding is large, the band limitation of the input signal is increased, and when the quantization width used in the past encoding is small, the band limitation of the input signal is weakened.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to a digital VTR.
The present invention relates to an encoding device used for high-efficiency encoding, such as an encoding device and a decoding device thereof, and methods thereof.

[0002]

2. Description of the Related Art With the digitization of image signals, high-efficiency coding techniques have become important. An effective means of high efficiency coding is orthogonal transform coding. The orthogonal transform converts an input time-series signal into an orthogonal component (for example, a frequency component). Fourier transform, discrete cosine transform (hereinafter abbreviated as DCT), and Hadamard transform are well known. In particular, DCT has attracted attention as an orthogonal transform suitable for image information.

[0003] Here, a high efficiency coding method using DCT will be described. FIG. 12 shows an example of a conventional high-efficiency coding apparatus using DCT. In FIG. 12, reference numeral 1 denotes input means of the apparatus, 2 denotes blocking means, 3 denotes DCT means, 4 denotes adaptive quantization means, 5 denotes variable length coding means, 6 denotes data buffer means, and 7 denotes output means.

[0004] In the encoder shown in FIG. 1, a digital image signal input from an input means 1 is converted into a DC signal by a blocking means 2.
Divide into blocks of T units. In high-efficiency coding of images, a two-dimensional DCT of a total of 64 pixels of 8 horizontal pixels and 8 vertical pixels
Is often used. Blocked image signal is DCT
The two-dimensional DCT is performed by the means 3 and converted into a DCT component.
The transformed DCT component is quantized by the adaptive quantization means 4, is variable-length coded by the variable-length coding means 5, is converted to a constant rate by the buffer means 6, and is output.

[0005] Variable length coding is a coding method in which a small code length is assigned to a code word having a large probability of occurrence, and a large code length is assigned to a code word having a low probability of occurrence. (Table 1) shows 3-bit data “0”, “1”,.
It is a correspondence table of variable length coding to "7". In this example, 2 bits for “0” and “1”, “2” and “3”
, A code length of 4 bits is assigned to “4”, “5”, “6”, and “7”.

[0006]

[Table 1] Normally, the DCT component has an exponential distribution centered on 0,
The occurrence probabilities of “0” and “1” are “4”, “5”, “6”,
This is considerably larger than “7”, and the average number of bits after encoding is smaller than 3 bits. However, when variable length coding is used, the data rate after coding changes depending on the image quality. Therefore, in the conventional example of FIG.
When the data amount in the buffer means 6 has increased in order to prevent overflow or underflow from occurring, the rounding at the time of quantization is increased in the adaptive quantization means 4 and the data amount has been reduced. In such a case, control is performed by reducing the roundness.

[0007]

Next, problems of the high efficiency coding using the conventional DCT as described above will be described below. (1) Since variable-length coding is used, if even a single bit error occurs on a transmission line, code synchronization is lost and subsequent data cannot be decoded. Such error propagation causes large image quality degradation. In particular, it is difficult to adapt to a device having a high error occurrence probability such as a VTR. (2) Conventionally, feedback control using a buffer unit is performed to keep the data amount constant. However, in an actual image, the information is biased, and it is difficult to perform optimal coding by feedback control. In particular, when the amount of information in the first half of the image is small and the amount of information in the second half is large, data is unnecessarily allocated to the first half, so that the amount of data is insufficient in the second half and the image quality is greatly deteriorated. (3) In the high-efficiency coding using orthogonal transform, when the information amount of an input image is large, distortion due to quantization increases and block distortion occurs.

An object of the present invention is to provide an orthogonal transform coding apparatus which solves the problems of the conventional orthogonal transform coding apparatus.

[0009]

According to a first aspect of the present invention, there is provided an encoding apparatus comprising: a pre-filter for restricting a transmission band of an input signal; The pre-filtering means strengthens the band limitation of the input signal when the quantization width used in the past encoding is large, and applies the quantization used in the past encoding. In the case where the band width is small, the band limitation of the input signal is weakened.

According to a second aspect of the present invention, there is provided a decoding apparatus which receives orthogonally transformed and quantized encoded data, decodes the input signal, and sets a transmission band of the decoded signal. Post-filter means for limiting,
The post-filter means strengthens the band limitation of the decoded signal when the quantization width used for past or current encoding is large, and sets the quantization width used for past or current encoding. Is smaller, the band limitation of the decoded signal is weakened.

According to a third aspect of the present invention, there is provided an encoding method for limiting a transmission band of an input signal, orthogonally transforming the band-limited signal, quantizing the signal, and encoding the signal. When the quantization width is large, the band limitation of the input signal is strengthened, and when the quantization width used in the past encoding is small, the band limitation of the input signal is weakened.

According to a fourth aspect of the present invention, there is provided a decoding method for inputting orthogonally transformed and quantized encoded data, decoding the input signal, and limiting a transmission band of the decoded signal. When the quantization width used for the past or current encoding is large, the band limitation of the decoded signal is strengthened, and when the quantization width used for the past or current encoding is small. Is characterized in that the band limitation of the decoded signal is weakened.

[0013]

Embodiments of the present invention will be described below with reference to the drawings.

FIG. 1 is a block diagram of an orthogonal transform coding apparatus according to one embodiment of the present invention. In FIG. 1, reference numeral 8 denotes human power means of the present invention, 9 denotes large block means, 10 denotes small block means, 11 denotes orthogonal transform means, 12 denotes data buffer means, 13 denotes data amount estimating means, and 14 denotes quantization means selection. Means, 15 means quantization means, 16 means variable length coding means, 1
7 is a transmission means, 18 is an output means.

First, the image signal input from the input means 8 is divided into large blocks consisting of a plurality of sample values by the large block forming means 9. Each large block is further divided into smaller blocks 1
It is divided into small blocks that become rectangular on the screen at 0. Here, in order to simplify the following description, a description will be given using a small block composed of 64 pixels consisting of 8 pixels in the horizontal direction and 8 pixels in the vertical direction on the screen. The sample values divided into small blocks are orthogonally transformed by the orthogonal transformation means 11 in both the horizontal and vertical directions.

FIG. 2 is an explanatory view of the orthogonal transform means 11. In FIG. 2, reference numeral 19 denotes an input means for sample values in small blocks;
Denotes DCT means in the horizontal direction, 21 denotes horizontal / vertical rearrangement means, 22 denotes DCT means in the vertical direction, and 23 denotes output means. The sample values divided into small blocks by the small block unit 10 in FIG. 1 are input from the input unit 19 in FIG. 2 and are DCT-horizontally performed by the DCT unit 20. The orthogonal components subjected to the DCT in the horizontal direction are rearranged in the vertical direction by the horizontal / vertical rearrangement unit 21. The rearranged orthogonal components are subjected to DCT in the vertical direction by the DCT means 22 and output. As shown in FIG. 3, the orthogonal components of each small block DCT-horizontally and vertically as described above are sequentially calculated from the orthogonal component representing the low frequency in both the horizontal direction and the vertical direction, as shown in FIG. Input to the means 13.

The data amount estimating means 13 calculates the data amount of each of a plurality of quantizers prepared in advance after encoding in small block units, and based on the calculation result, the quantizing means selecting means 14 calculates the data amount. A quantizer is selected for each small block. At the same time, the orthogonal components input to the buffer means 12 are delayed until the quantizer is determined. Here, the relationship between the quantized orthogonal components and the data amount after encoding will be described with reference to FIG.

In the first transmission means of the present invention, the lowest horizontal and vertical frequency components (quantized values of horizontal 0 and vertical 0 in FIG. 4, hereinafter referred to as the origin) are defined as one vertex and all 0 (See Fig. 4)
(The part surrounded by the solid line). However, the origin shall always be transmitted. Accordingly, the transmission area (rectangle in FIG. 4) of this block is determined by the position of the quantization value representing the highest non-zero frequency component in each of the horizontal direction and the vertical direction. Since the number of quantization values transmitted simultaneously is determined by the area of this transmission area, it can be easily calculated by the product of the position of the highest frequency in the horizontal direction and the position of the highest frequency in the vertical direction. Further, in this embodiment, the information of the transmission area can be represented by a total of 6 bits of 3 bits in the horizontal direction and 3 bits in the vertical direction as shown in FIG. Therefore, the encoded data amount of each small block is the sum of the variable length codeword included in the transmission area and the information of the transmission area.

Here, the first variable length coding method of the present invention will be described. Here, a variable length code whose code length is 1 bit when the quantization value is 0 is used. That is, for a certain quantized value Ri, the code length Ni becomes Ni = 1 when Ri = 0. Therefore, by adding the number of quantized values to be transmitted and the 6-bit coordinate of the vertex of the rectangle to the sum of (Ni-1) for all the quantized values for one small block, Is required. Therefore, in the calculation of the data amount, the calculation of the sum of the code lengths and the calculation of the transmission area can be executed independently, so that the circuit can be simplified and the speed can be increased. It is also possible to assign fixed-length coding to a quantization value representing the lowest frequency in both the horizontal and vertical directions.

The data amount for each quantized value in the small block unit thus obtained is determined by the quantizing means selecting means 1.
4 is input. Therefore, a sub-quantity unit is determined in small block units so as not to exceed a predetermined transmission data amount in a large block. Then, based on this, it is quantized by the quantizer 15, variable-length coded by the variable-length coding means 16, and output to the transmission means 17. At the same time, the transmission area (6 bits) of each small block for the selected quantizer is transmitted at the same time.

As described above, according to the present invention, it is possible to always select an optimum quantizer by estimating the data amount before quantization. Further, unlike the conventional feedback control, since the data amount can be accurately controlled, it is possible to perform variable-length encoding such that the length becomes constant within a small range. As a result, it becomes possible to use variable-length coding for a device such as a digital VTR in which transmission path errors frequently occur. Further, in the above embodiment, the description is made using the two-dimensional DCT, but various other orthogonal transforms are applicable, and a three-dimensional orthogonal transform including the time axis direction can also be used. In the simplest example of the three-dimensional orthogonal transform, there is a method of calculating a sum and a difference between two fields of two orthogonal orthogonally transformed orthogonal components between fields at the same spatial position. In this case, the sum component is quantized by a quantizer having a small quantization width, and the difference component is quantized by a quantizer having a large quantization width, so that the data amount is suppressed while suppressing visual distortion. Can be compressed.
In addition, regarding the above-mentioned transmission region, by independently obtaining the sum component and the difference component, it becomes possible to more efficiently remove the quantization value of 0 generated in the difference component.

Next, an embodiment using the second variable length coding will be described. First, the assignment of variable length coding is shown in (Table 2).

X in Table 2 is assigned an arbitrary 1-bit number. For example, Table 3 shows an example of a code word having a code length of 5 bits.

In the variable length coding shown in Table 2, the code length Ni is represented by Ni = 2 × Ki + 1 with respect to the number of digits Ki of the absolute value of the quantization value. Therefore, the code length can be easily calculated by obtaining the number of digits of the quantization value. Accordingly, the total data amount D of the small block to be transmitted is represented by D = 2 × ΣKi + M + 6 together with the number M of the quantized values to be transmitted and the 6-bit coordinates of the vertices of the rectangle, and can be easily obtained. . Also, in the variable length code of (Table 2), the part of ± 128-255 is
It is also possible to change to XXXXXXX.

[0025]

[Table 2]

[0026]

[Table 3] Next, an embodiment of the third variable length coding is shown in (Table 4).
In this embodiment, it is possible to determine the code length of only the first half of a code word, similarly to the variable length coding of (Table 2). The use of such a variable length code has a feature that even if an error occurs in the transmission path, word synchronization is not lost unless the first half representing the code length is erroneous.

Since the code length can be easily detected at the time of variable-length decoding, high-speed decoding can be performed with a simple circuit.

[0028]

[Table 4] Next, a fourth variable length coding method will be described. Most of the orthogonally transformed components have quantization values of 0.
Therefore, there is a high probability that a quantized value of 0 is continuously generated.
Therefore, the data amount can be compressed by run-length encoding the continuous length of the quantized value of 0. Furthermore, by compressing the length of the continuous quantized value of 0 and the first non-zero quantized value following it into one codeword, it is possible to perform more efficient compression. This is called two-dimensional run-length encoding. Where 2
Transmission means for more efficiently performing dimensional run-length encoding will be described.

FIG. 5 shows an embodiment of the second transmission means of the present invention. In the present embodiment, the orthogonally transformed components are coded and transmitted in the order of the numbers in FIG. 5 in order from the quantized value representing the lowest horizontal and vertical frequency components in the small block, and transmitted. Is replaced with a codeword representing the end signal. As a result, high-frequency portions having a high probability of occurrence of zeros can be concentrated in the latter half, so that the length of consecutive zeros can be further lengthened. There is also a method that does not use the above terminator.

FIG. 6 shows an embodiment of the third transmission means of the present invention. FIG. 6 shows an embodiment in which a large block is composed of three small blocks. As shown in FIG. 5, the upper left of each small block represents an orthogonal component representing a low band, and the lower right represents an orthogonal component representing a high band. FIG.
The number indicates the transmission order of the orthogonal component at that position,
Data is transmitted in large block units in order from the low frequency component. With such a transmission order, high frequency components can be concentrated in the latter half in large block units. Therefore, it becomes possible to make the continuation of 0 longer. FIG. 7 shows a specific example of the first and third transmission means. In the transmission means as described above, when the amount of data after encoding is too large to transmit all codewords, a high-frequency component whose transmission order is later cannot be transmitted. However, in general, the distortion of the high-frequency component is hardly visually noticeable, so that it is possible to minimize the image quality deterioration. Further, even when an error occurs in the transmission path and the word synchronization is lost, and the latter code word cannot be decoded, the influence concentrates on a high frequency band, so that visual deterioration can be reduced.
These transmission orders can also be applied to the first transmission means. FIG. 4 is an example in which the third transmission order is applied to the first transmission means. In FIG. 4, transmission is performed in order from the low-frequency component in units of large blocks, and only the portion surrounded by the square representing the transmission area is transmitted as described in the first transmission means. Further, as the actual transmission order, various orders other than FIGS. 5 and 6 are possible.

Next, the large block means 9 of the present invention will be described. First, the first large block forming means is to form a large block only with data in a field. This makes it possible to configure a large block with only a small memory in the field.

The second large block forming means comprises a large block composed of signals between a plurality of continuous fields, contrary to the first block. As a result, compression utilizing redundancy between fields of an image can be performed, so that a higher compression ratio can be realized.

The third large block forming means comprises a large block from signals adjacent on the screen. This enables compression utilizing the redundancy between small blocks. In particular, the efficiency can be improved in the case of encoding transmission in units of large blocks as in the above third transmission means.

The fourth large block forming means is constituted by collecting large blocks by shuffling signals at various positions on the screen in small block units. As a result, the amount of information on the screen is dispersed, so that the amount of information included in each large block is approximately equal. Therefore, even when the amount of information is uneven depending on the location on the screen, it is possible to efficiently compress the information. Further, since the data rate after compression is also averaged, it is easy to control the same data amount in large block units.

In the fifth large block forming means, when the input signal is composed of a luminance signal and a chrominance signal, for example, a chrominance signal, all the large blocks have the luminance signal and the chrominance signal mixed at almost the same ratio. Constitute in shape. Generally, there is a bias in the information amount of the luminance signal and the color difference signal. Thus, as described above, since each large block includes the luminance signal and the chrominance signal at the same ratio, the information amount can be averaged similarly to the fourth large block forming unit. Even when the input signals are R, G, and B signals, the information amount can be averaged by configuring all the large blocks in such a manner that the R, G, and B signals are mixed at almost the same ratio. Will be possible.

Next, the miniaturization means 10 of the present invention will be described. The first sub-blocking means is a sub-block composed of only sub-field signals. With this method, the small block and the large block can be constituted only by the small memories in the field, so that the circuit scale can be reduced. In the case of a moving image having a lot of motion, the distortion can be suppressed by the in-field processing.

The second sub-blocking means comprises a sub-block composed of signals between a plurality of continuous fields. By configuring a small block with a signal included in a plurality of fields, it is possible to perform compression for removing redundancy between fields. This is particularly effective for moving images with small movements.

The third sub-block forming means adaptively switches, for each sub-block, whether the sub-block is composed of only a signal in one field or one frame or a signal of a plurality of continuous fields. This makes it possible to compress small moving blocks and still images with small distortion by configuring small blocks with fast movement in a field and small blocks with small movement in two or more fields.

Next, the quantization means 15 of the present invention will be described. In the first quantization means, a plurality of quantizers have different quantization widths. This makes it possible to change the amount of encoded data for each quantizer. Therefore, by controlling the quantizer, it becomes possible to control the data amount after encoding.

The second quantization means allocates a large quantization width to the orthogonal component representing the high frequency band, and allocates a smaller quantization width to the quantization component representing the low frequency band. This makes it possible to concentrate the quantization distortion in the high frequency region,
Visual quality degradation and block distortion due to orthogonal transform can be improved. Further, in the first quantizing means, more efficient compression can be performed by increasing the difference between the higher band quantization width and the lower band quantization width for a quantizer having a larger quantization width.

In the third quantization means, at the time of quantization, the average value of the quantization error of the quantization value quantized to a value other than 0 for each small block is calculated, and transmitted together with the quantization value. .

The quantization error of the orthogonal transform often has a bias in small block units. Therefore, it is possible to improve the quantization distortion by calculating the quantization error for each small block and correcting it at the time of decoding.

Since the quantization error signal transmitted at this time can be represented by several bits for one small block, the increase in the data amount is extremely small.

The fourth quantization means quantizes small blocks located at the same position in the frame or field direction using a quantizer having a different quantization characteristic for each frame or field.

By using the fact that the quantized value transmitted for each frame or field differs for the same orthogonal component, an optimal quantized representative value can be set.

Therefore, it is possible to reduce a quantization error in a moving image having a small motion.

Next, the quantization means selection means 14 of the present invention will be described.

The first quantizing means selecting means 14 obtains the coded data amount for all the quantizers for each small block based on the data amount estimating means 13 as described above.

Then, a quantizer is selected in small block units so that the amount of data can be transmitted in large block units. This prevents overflow after encoding and a shortage of data to be transmitted.

When there are m quantizing means candidates, the second quantizing means selecting means 14 first determines that the coded data amount of the m quantizers is approximately m / m. The data of the second quantizer is estimated.

If the value is larger than the amount of data that can be transmitted, only quantizers having a data amount smaller than the quantizer for which the data amount has been estimated are used as quantization means candidates.

On the contrary, when the data amount is smaller than the data amount that can be transmitted, only the quantizer having a data amount larger than the quantizer which is a candidate for the quantizing means is used.

In this way, the estimation of the data amount is repeated while reducing the number of quantization candidates to about 1/2 each time the estimation of the data amount is performed, and the optimum quantizer is selected.

According to this method, when the number of quantization means candidates is 7, the optimum quantizer can be selected by estimating the data amount three times.

As described above, the second quantization means selection means 14
Thus, the amount of calculation required for estimating the amount of data can be significantly reduced.

The third quantizing means selecting means 14 divides the small block included in the large block into two parts, the former part from the front to the j-th part and the latter half part thereafter. The two quantizing means having the closest data amount after encoding are selected, and at the time of transmission, the quantizing means used in the first half or the second half and the information of the value of j are encoded and transmitted.
The first quantization means selection means 14 can freely select a quantizer for each small block. Therefore, the number of combinations of quantizers is very large in large block units, and a large amount of calculation is required to calculate the data amount for all combinations.

Therefore, the third quantization means selection means 14 uses only two types of quantizers in one large block as described above. Due to this limitation, the number of combinations of the quantizers in the large block is greatly reduced, so that the calculation amount can be reduced.
The two types of quantizers are also divided into the first half small block and the second half small block in the large block and assigned. For this reason, information on which quantizer is used only needs to be transmitted at the position of the first half and the second half of the large block (that is, j), so that the increase in the data amount is small.

The fourth quantizing means selecting means 14 provides the maximum quantized absolute value of the orthogonal component for each small block to two types of quantizers having different quantization widths, each having the closest data amount after encoding. Detect a value, select a quantizer with a large quantization width for a small block with a large maximum value, select a quantizer with a small quantization width for a small block, and select either one during transmission. And information indicating which quantizer each small block has selected is quantized and transmitted simultaneously. Generally, in an image having a large dynamic range, the deterioration is hardly recognized visually, and in an image having a small dynamic range, the deterioration is easily detected. Therefore, as described above, the maximum value of the absolute value of the quantization value (dynamic range)
By assigning a quantizer having a large quantization width to a small block having a large size, large compression can be performed while suppressing visual deterioration.

Here, another embodiment of the present invention will be described. FIG. 8 is a block diagram of the encoding part of the present invention. In FIG. 8, reference numeral 24 denotes an input means, 25 denotes a pre-filter, and 26 denotes a first filter.
The orthogonal transform encoding means of the present invention described in the above embodiments, 2
Reference numeral 7 denotes an output unit. In the embodiment shown in FIG.
4 is first band-limited using the pre-filter 25. The band-limited signal is encoded by the orthogonal transform encoding unit 26 in the same manner as in the above-described embodiment, and is output to the output unit 27. By limiting the band using the pre-filter before performing the orthogonal transform coding, it is possible to improve image quality deterioration such as block distortion due to compression.

FIG. 9 is a block diagram of the decoding part of the present invention. In FIG. 9, reference numeral 28 denotes an input means, 29 denotes a decoding means for the orthogonal transform coding apparatus of the present invention described in the above embodiment, and 30 denotes a rear part. The filter 31 is an output means. FIG.
In the embodiment, first, the codeword input from the input unit 28 is decoded by the orthogonal transform decoding unit 29. The decoded signal is output to output means 31 via post-filter 30. By limiting the band of the decoded signal using a post-filter, it is possible to improve image quality deterioration such as block distortion due to compression. When a pre-filter is used at the time of encoding, a band limited at the time of encoding can be reproduced by using a filter having the opposite characteristic as the post-filter.

Next, the pre-filter means 25 will be described. The first pre-filter means compresses vertical, horizontal, or oblique high frequency components of the input signal. In the above-described transmission means of the present invention, when the quantization value representing the vertical, horizontal, or oblique high-frequency component becomes 0, significant compression becomes possible.
At the same time, the distortion of the high frequency component is hardly detected visually. Therefore, by using such a pre-filter, it is possible to reduce the data amount while suppressing the image quality deterioration.

The second pre-filter means converts the input signal into four bands, low and high in both horizontal and vertical directions, high in horizontal and low in vertical, low in horizontal and high in vertical, and high in both horizontal and vertical. And linearly compress each band independently, and then add all the bands. An embodiment of this pre-filter will be described with reference to FIG. 10, 32 is an input means of this filter, 33 is a vertical low-pass filter (hereinafter referred to as LPF), 34 and 35 are horizontal LPFs, 36, 37 and 38 are subtracters, 39, 40 and 41 are linear compression means, 42 is an adder and 43 is an output means.

The signal input from the input means 32 is vertical L
The signal is converted to a low-frequency component in the vertical direction by the PF 33. Vertical LP
The output of F33 is subtracted from the input by a subtractor 36. As a result, the output of the vertical LPF 33 represents the reduced component in the vertical direction of the input signal, and represents the vertical high-frequency component of the output signal of the subtractor 36. Similarly, the horizontal LPFs 34 and 35 and the subtracters 37 and 38 can be used for these two outputs to further divide the band in the horizontal direction. FIG. 11 is an explanatory diagram of two-dimensional band division. Horizontal L in FIG.
The output of the PF 34 indicates a portion represented by LL in FIG.
The output of the subtractor 37 in FIG. 10 indicates a portion represented by LH in FIG. 11, and the output of the horizontal LPF 35 in FIG.
11 shows a portion represented by L, and the output of the subtractor 38 in FIG. 10 shows a portion represented by HH in FIG.

The bands thus divided into four bands in two dimensions are the compression means 39, 4 shown in FIG. 10 except for the LL component.
Linear compression is performed at 0,41. The components compressed for each frequency are added by the adder 42, returned to one signal, and output from the output means 43. In this way, by dividing the band into two-dimensional bands and then compressing the band, it is possible to limit the band in accordance with human visual characteristics. In particular, the data amount can be efficiently reduced by greatly compressing the HH component in which the visual deterioration is hardly detected. Further, since the pre-filter uses linear compression, it is possible to relatively easily restore the band by the post-filter at the time of decoding.

The third pre-filter means uses nonlinear compression for compression of each band in the second pre-filter means. Human vision is insensitive to large amplitude distortion of high frequency components. Therefore, a component having a larger amplitude is subjected to a larger compression by nonlinear compression. As a result, the distortion can be concentrated on the high-frequency component having a large amplitude.

The fourth prefilter means in the second or third prefilter means sets a threshold value for each band after band division and rounds a value smaller than the threshold value to zero. In human vision, a small amplitude of a high frequency component is recognized as noise, so that even if the component is removed, the effect is small. Therefore, by removing components smaller than the threshold value, the amount of unnecessary information can be reduced. The fifth pre-filter means controls the frequency characteristics of the pre-filter means by using the quantization information of the data which has already been subjected to the orthogonal transform coding. When a quantizer with a large quantization width is selected in the orthogonal transform coding, it indicates that the input information amount is large and distortion due to compression is large.
Conversely, when a quantizer with a small quantization width is selected, it indicates that input information is small and distortion due to compression is small. Therefore, when the quantization width selected in the past is large, the band limitation by the pre-filter is strengthened to reduce the amount of input information. Conversely, when the quantization width selected in the past is small, the band limitation by the pre-filter can be reduced and the distortion by the pre-filter can be reduced. This makes it possible to encode more faithfully in an image with a small amount of input information, and to suppress a visual deterioration by a pre-filter in an image with a large amount of input information.

Next, the post-filter means 30 will be described. The first post-filter means compresses or expands a vertical, horizontal, or oblique high frequency component of the input signal. In orthogonal transform coding, the influence of quantization distortion appears as block distortion between small blocks. Therefore, it is possible to improve the block distortion by compressing the high-frequency component at the block boundary by the post-filter. If the band is limited by a pre-filter at the time of encoding, it is possible to reproduce the limited band by expanding the high-frequency component.

The second post-filter means performs filtering by using a signal which is transmitted between fields or between frames. As a result, a filter for suppressing a difference signal between fields or between frames can be configured. This makes it possible to greatly reduce distortion due to compression in a moving image with small motion.

The third post-filter means reduces the input signal in both the horizontal and vertical directions, and reduces the input signal into four bands, ie, a high horizontal band and a vertical low band, a horizontal low band and a vertical high band, and a horizontal and vertical high band. Divide and independently compress or decompress each band, then add all bands. The configuration of the post-filter can be realized by the same circuit as the pre-filter of FIG. By compressing the band after dividing it in this way, it is possible to remove the compression distortion in accordance with the visual characteristics. The second
When the pre-filter means is used, it is possible to reproduce the limited band by extending each band with the inverse characteristic.

The fourth post-filter means uses nonlinear expansion for expansion of each band in the third post-filter means. When the high-frequency component is linearly extended as in the case of the third post filter, block distortion may be amplified. Therefore, non-linear expansion is performed to expand only large high-frequency components without expanding small high-frequency components.

Generally, since the amplitude component of block distortion is small, this method makes it possible to restore a band without amplifying block distortion.

The fifth post-filter means in the second, third or fourth post-filter means sets a threshold value for each band after band division and rounds a value smaller than the threshold value to zero. In human vision, a small amplitude of a high frequency component is recognized as noise, so that even if the component is removed, the effect is small. Therefore, unnecessary information can be reduced by removing components smaller than the threshold value. At the same time, it is possible to remove block distortion.

The sixth post-filter means controls the frequency characteristic of the post-filter means based on the quantization information of the transmitted data. When a quantizer having a large quantization width is selected in the orthogonal transform coding, the quantization distortion is large. For this reason, the effect of quantization distortion can be reduced by increasing the band limitation by the post-filter. Conversely, when a quantizer with a small quantization width is selected, it indicates that distortion due to compression is small. Therefore, the band limitation can be reduced to reduce the distortion caused by the post-filter. When the fifth pre-filter is used at the time of encoding, it is possible to estimate what pre-filter is used by the selected quantizer. Therefore, by using a filter having a characteristic opposite to that of the pre-filter by the post-filter, it becomes possible to restore the limited band.

[0074]

As described above, according to the present invention, it is possible to always select an optimal quantizer by estimating the data amount before quantization. Also, unlike conventional feedback control, the amount of data can be controlled accurately,
It is possible to perform variable length encoding so that the length becomes constant within a small range. As a result, it becomes possible to use variable-length coding for a device such as a digital VTR in which transmission path errors frequently occur.

[Brief description of the drawings]

FIG. 1 is a block diagram of an embodiment of an orthogonal transform coding apparatus according to the present invention.

FIG. 2 is a block diagram of a two-dimensional orthogonal transform unit according to the embodiment;

FIG. 3 is a configuration diagram for explaining orthogonal components subjected to two-dimensional orthogonal transformation in the embodiment.

FIG. 4 is a configuration diagram for explaining a first transmission unit according to the embodiment;

FIG. 5 is a configuration diagram for explaining a second transmission unit according to another embodiment.

FIG. 6 is a configuration diagram for explaining a third transmission unit according to another embodiment.

FIG. 7 is a configuration diagram showing a specific example of first and third transmission means according to the embodiment;

FIG. 8 is a block diagram of a pre-filter according to another embodiment.

FIG. 9 is a block diagram of a post filter according to another embodiment.

FIG. 10 is a circuit diagram of a pre-filter according to another embodiment.

FIG. 11 is a configuration diagram for explaining band division of the pre-filter according to the embodiment.

FIG. 12 is a block diagram of a conventional orthogonal transform coding apparatus.

[Explanation of symbols]

 Reference Signs List 8 input means 9 large blocking means 10 small blocking means 11 orthogonal transform means 12 buffer means 13 data estimation means 14 quantization means selection means 15 quantization means 16 variable length coding means 17 transmission means 18 output means

Claims (4)

[Claims] 1. A pre-filter comprising: a pre-filter for limiting a transmission band of an input signal; and an orthogonal transform encoder for quantizing and encoding an output of the pre-filter after orthogonal transform. The means strengthens the band limitation of the input signal when the quantization width used in the past encoding is large,
An encoding apparatus, wherein when the quantization width used in past encoding is small, the band limitation of the input signal is weakened. 2. An orthogonal transform decoding means for inputting orthogonally transformed and quantized and encoded data and decoding the input signal, and a post-filter means for limiting a transmission band of the decoded signal. The post-filter unit, if the quantization width used in the past or current encoding is large, strengthens the band limitation of the decoded signal, and sets the quantization used in the past or current encoding. A decoding apparatus characterized by weakening the band limitation of the decoded signal when the decoding width is small. 3. A method for limiting a transmission band of an input signal, orthogonally transforming the band-limited signal, quantizing the encoded signal, and encoding the encoded signal when a quantization width used in past encoding is large. Encoding method, wherein the band limitation of the input signal is strengthened, and the band limitation of the input signal is weakened when the quantization width used in past encoding is small. 4. A decoding method for inputting orthogonally transformed and quantized and encoded data, decoding the input signal, and limiting a transmission band of the decoded signal. When the quantization width used for encoding is large, the band limitation of the decoded signal is strengthened, and when the quantization width used for past or current encoding is small, the A decoding method characterized by weakening a band limit.