JPH0851599A - Image information conversion device - Google Patents

Abstract

(57) [Abstract] [Purpose] The supplied image signal can be converted into an image signal with higher resolution. [Structure] An SD image supplied to a region dividing circuit 2 is divided into predetermined regions and supplied to an ADRC circuit 3 and a delay circuit 8. Similarly, the area division circuit 4 to which the SD image is supplied divides the area into a range larger than the area division circuit 2 and supplies the area to the motion class determination circuit 5. In the class code generation circuit 6, the area pattern is supplied from the ADRC circuit 3 and the motion class mv-class is supplied from the motion class determination circuit 5, and integrated to generate a final class code class. In the ROM table 7, the class code generation circuit 6
The coefficient data is read out based on the class code class supplied from, and supplied to the estimation calculation circuit 9. In the estimation calculation circuit 9, vertical interpolation is performed from the supplied coefficient data and pixel values. Similarly, in the horizontal interpolation filter 10, horizontal interpolation is performed and an HD image is extracted.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image information conversion device suitable for use in, for example, a television receiver, a video tape recorder device, and the like, and particularly to a high resolution image information of ordinary resolution supplied from the outside. The present invention relates to an image information conversion device that converts the image information into image information and outputs the image information.

[0002]

2. Description of the Related Art Nowadays, due to the increasing audio-visual orientation, it is desired to develop a television receiver capable of obtaining a higher resolution image. In response to this demand, a so-called high-definition system has been developed. It was
This high-definition system has a scanning line number of 525 defined by the so-called NTSC system, but it is more than twice as large as one.
In addition to the 125 lines, the aspect ratio of the display screen is NTS
The C method is 3: 4, while the high-definition method is 9:16.
And a wide-angle screen. Therefore, it is possible to obtain a high-resolution and realistic screen.

Although the high-definition system has such excellent characteristics, it is impossible to display an image even if the video signal of the NTSC system is supplied as it is. This is because the standards are different between the NTSC system and the high-definition system as described above. For this reason, when displaying an image corresponding to the NTSC video signal in the high-definition system, conventionally, for example, an image information conversion device as shown in FIG. 9 is used to perform rate conversion of the video signal.

In FIG. 9, a conventional image information conversion apparatus includes a horizontal interpolation filter 42 for performing horizontal interpolation processing on an NTSC video signal supplied through an input terminal 41, and a horizontal interpolation filter. A high-definition video signal can be obtained from the output terminal 44, which is composed of a vertical interpolation filter 43 that performs vertical interpolation processing on the processed video signal.

Specifically, the horizontal interpolation filter 42 has a structure as shown in FIG. 10, and the video signal of the video system supplied through the input terminal 41 is supplied to the first through the input terminal 51. It is supplied to the 1st to the m-th multipliers 52 to 52m, respectively. Each multiplier 52 multiplies the video signal by coefficient data and outputs the result. The video signals multiplied by the coefficient data are supplied to the first to mth adders 53 to 53m-1, respectively. Between each adder 53-53m-1, the time T
Delay registers 54 to 54m are provided. Then, the video signal output from the m-th multiplier 52m is delayed by the time T by the m-th delay register 54m,
1 is supplied to the adder 53m-1.

The (m-1) th adder 53m-1 receives the video signal delayed by the time T from the mth delay register 54m and the video signal from the m-1th multiplier 52m-1. And are added and output. The video signal on which this addition processing has been performed is again delayed by the time T by the (m-1) th delay register 54m-1, and the (m-2) th adder 53 (not shown).
m−2, the m−th multiplier 53 (not shown)
Addition processing is performed with the video signal from m-2. The horizontal interpolation filter 42 thus supplies the NTSC video signal to the vertical interpolation filter 43 via the output terminal 55.

The vertical interpolation filter 43 has the same configuration as the horizontal interpolation filter 42 described above, and performs vertical pixel interpolation on the video signal subjected to the horizontal interpolation processing. As a result, vertical pixel interpolation is performed on the NTSC video signal. The converted high-definition video signal is supplied to the high-definition receiver. As a result, an image corresponding to the NTSC video signal can be displayed on the high-definition receiver.

[0008]

However, the above-mentioned conventional image information conversion apparatus merely interpolates in the horizontal direction and the vertical direction based on the video signal of the NTSC system, and therefore the resolution is high. Is no different from the original NTSC video signal. In particular, when a normal moving image is a conversion target, vertical interpolation is generally performed by intra-field processing, but in the case of the image conversion shown in FIG. 9, there is no inter-field correlation of images. Therefore, in the image static unit, there is a drawback that the resolution is deteriorated rather than the video signal of the NTSC system due to conversion loss.

On the other hand, class division is performed according to the three-dimensional (spatiotemporal) distribution of the image signal level as the input signal,
For each class, there is a storage unit that stores a prediction coefficient value acquired by learning in advance, and outputs an optimum estimated value by a calculation based on a prediction formula.

According to this method, when creating HD (High Definition) pixels, SD (Standerd Def) in the same frame which is continuous in the vertical direction in the vicinity of the HD pixel to be created.
inition) Pixels are divided into classes, and the prediction coefficient value is acquired by learning for each class. By using intra-frame correlation in the image still part and intra-field correlation in the motion part, the true value can be made more accurate. The trick is to get close HD pixels.

For example, in FIG. 11, SD pixels x ₁ to
When x ₆ is used for class classification, the quantized data obtained as a result of performing 2-bit ADRC on SD pixels x _{1 to} x ₆ are 3, 0, 3, 0, 3, 0 in that order. ,
The part is very likely to be a moving image. That is, it is highly possible that the image around the HD pixel y to be created is moving. Therefore, in the image signal conversion device, SD pixels x ₂ and SD that are close in spatial position in the temporally equal data are used.
The HD pixel y is created by focusing on the pixel x ₄ .

On the other hand, when the quantized data as a result of performing 2-bit ADRC on the SD pixels x _{1 to} x ₆ are 3, 3, 2, 2, 1, 0, respectively, that part is It is likely to be a still image. Therefore, in the image signal conversion device, regardless of the temporal phase, SDs with close spatial positions are used.
The HD pixel y is created by focusing on the pixel x ₂ and the SD pixel x ₄ . At this time, the class classification is with / without motion,
In addition to expressing the signal waveforms in the vicinity of the HD pixel to be created, it is also a great feature to output the optimum prediction coefficient value for each waveform.

According to this method, the switching between still / moving can be smoothly expressed by learning by using an actual image, so that it is unnatural due to the switching between still / moving as in the conventional motion adaptive method. It is possible to significantly reduce the occurrence of the sag.

However, in the above method, it is necessary to express two pieces of motion information and a waveform in space by dividing a finite number of classes, and depending on the class, the patterns that should be separated should be included in one class. There were cases where they were mixed.

For example, when the quantized codes as a result of performing 2-bit ADRC on the above SD pixels x _{1 to} x ₆ are 3, 0, 3, 0, 3, 0 respectively, As described above, in the case of this pattern, the probability that the portion is a moving image is extremely high. However, if the spatial frequency is rarely high, such a pattern may appear even if there is no motion. In this case, a fine horizontal stripe pattern corresponds to it. In such a case, processing for moving images is performed even for a fine horizontal stripe pattern that is stationary, that is, conversion is performed using data that is spatially close in the same phase in time. However, this causes deterioration in resolution. There was something to do.

On the other hand, in the image signal conversion apparatus described in Japanese Patent Application No. 5-172617, the data for three fields is used, and the value of the data at the spatially same position is used to classify There is a method of classifying. For example, as shown in FIG. 12, in addition to SD pixels x ₁ ~x _6, to classification by adding even a SD pixels x ₇ in SD pixel x ₃ spatially same position, is that.

According to this method, in addition to the motion representation by the pattern of the data obtained by quantizing the SD pixels x _{1 to} x ₆ , SD is added.
It is possible to use motion representation by data obtained by quantizing the pixel x ₁ and the SD pixel x ₇ . That is, in FIG. 12, when the difference value between the SD pixel x ₁ and the SD pixel x ₇ is small, there is a high possibility that the image around the HD pixel y to be created is still. Therefore, in the above-mentioned image signal conversion device,
The HD pixel y is created by focusing on the SD pixel x ₁ and the SD pixel x ₂ which are close in spatial position. On the other hand, SD pixel x ₁ and S
HD that should be created when the difference value of D pixels x ₇ is large
The image around the pixel y is highly likely to be moving. Therefore,
In the image signal conversion device described above, the SD pixels x
Create HD pixel y by focusing on ₃ and SD pixel x ₄ .

However, S which are spatially in phase
If there is only one set of D pixel data, malfunctions are likely to occur due to the type of motion or the influence of noise, etc. Therefore, in order to further improve performance, two or more sets of SD pixels that are in the same phase in space are used. It is desirable to use data.

If there is a quick motion in the image,
For example, when the motion intervenes in only one field in the image, it may be difficult in principle to detect it by the above method. That is, when a moving object passes only in the # (k + 1) field in FIG. 12, SD pixel x ₁ and SD pixel x ₇
Since the difference value of is small, the static processing is performed on the pattern. Therefore, in this sense, it is desirable that SD pixel data sets that are spatially in the same phase exist in a temporally different combination.

As a countermeasure against this, a method of reducing the quality deterioration of the restored image by increasing the number of pixels used for the class division and increasing the number of classes can be considered. For example, SD pixels x ₃ spatially SD pixels x ₇ in the same position, not only, as shown in FIG. 13, SD pixels x ₂
SD pixel x ₈ and SD pixel x ₄ spatially at the same position as
It is conceivable to add a SD pixel x ₉ at the same spatial position as the above. According to this method, the number of sets of SD pixel data that are spatially in the same phase is increased, so that the performance of motion determination based on the pattern is improved.

However, if the added 3 pixels are quantized, for example, if 2-bit ADRC is performed in the same manner as other pixels, the number of classes will be 64 times that of the original method shown in FIG. The number becomes very large, resulting in an increase in hardware scale, which is not realistic.

Therefore, the object of the present invention is made in view of the above-mentioned problems, and image information capable of converting an NTSC video signal into a high-definition video signal with improved resolution. It is to provide a conversion device.

[0023]

SUMMARY OF THE INVENTION According to the present invention, in an image information converting apparatus for converting a digital image signal into a digital image signal having a larger number of pixels, the image information supplied from the outside is transferred in the same frame data. A first image information dividing unit that divides the image into a plurality of blocks, and a level distribution pattern is detected for each of the blocks divided by the first image information dividing unit, and based on the detected pattern, for each block A class detecting unit that outputs class detection information by determining the class to which the class belongs and image information supplied from the outside are divided into a plurality of blocks that are composed of a plurality of interframe data at the same spatial position.
Of the image information dividing unit and the second image information dividing unit calculates the average value of the absolute values of the inter-frame differences for each of the blocks divided, and based on a preset threshold value, a class representing a motion is determined. The motion class detecting means for outputting the motion class detecting information by determining, the class code generating means for integrating the information of the class detecting means and the motion class detecting means to determine the final class, and the externally supplied Coefficient data for storing the coefficient data of the estimation formula, which is information for converting the image information into the image information having a resolution higher than that of the image information, and outputting the coefficient data according to the class from the class code generating means. The image information supplied from the outside is converted into image information having a higher resolution than the image information according to the coefficient data from the storage means and the coefficient data storage means, and the image information is output. A picture information converting apparatus, comprising an image converting means for.

[0024]

The image information converting apparatus according to the present invention is provided with an input SD
The signal is divided by the image information dividing means into a plurality of regions consisting of a plurality of pixels in the same frame that are continuous in the vertical direction, a pattern of the level distribution of image information is detected for each region, and the detected pattern is detected. Based on the above, the class to which the image information of the area belongs is determined and the class detection information is output. Further, the image information dividing means of different types divides into a combination of a plurality of inter-frame data, the absolute value of the inter-frame difference at the spatially same position is calculated for each area, and the preset threshold value is set. The class indicating the degree of movement is determined by, and class detection information is output. The above two classes are integrated by the class code generating means and output as the final class.
The coefficient data storage means stores, for each class, coefficient data of a linear estimation formula that is information for converting image information supplied from the outside into image information having a resolution higher than this image information. The coefficient data is output according to the class detection information. Then, in the image information conversion means, according to the coefficient data supplied from the coefficient data storage means,
The image information supplied from the outside is converted into image information having a higher resolution than the image information supplied from the outside.

[0025]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of an image signal conversion device according to the present invention will be described in detail below with reference to the drawings. FIG. 1 shows a schematic configuration of signal processing of this embodiment, that is, an image signal conversion apparatus. The input terminal indicated by 1 is, for example, so-called NTSC as image information supplied from the outside.
A video signal of the system is supplied as digitalized SD pixels.

The positional relationship between SD pixels and HD pixels to be created in this embodiment is shown in FIG. That is, the HD pixels to be created include HD pixels y ₁ and S existing near the SD pixel when viewed in the same field.
There are two types, HD pixel y ₂ existing at a position far from the D pixel. Hereinafter, the mode for estimating the HD pixel y ₁ existing at a position close to the SD pixel is referred to as mode 1, and the mode for estimating the HD pixel y ₂ existing at a position far from the SD pixel is referred to as mode 2.

The area dividing circuit 2 divides the SD image signal supplied from the input terminal 1 into a plurality of areas. In this embodiment, SD pixels, for example, upper and lower 3 pixels in the same frame of HD pixels to be created, are divided into areas of 1 pixel × 6 lines, totaling 6 pixels.

Regarding mode 1, SD pixels x ₁ , x ₂ , x ₃ , x ₄ , x for HD pixel y ₁ in FIG.
₅ and x ₆ correspond to the area. This area will be called block 1. Regarding mode 2, H in FIG.
SD pixels x ₁ , x ₂ , x ₃ , x for D pixel y ₂ .
₄ , x ₅ and x ₆ correspond to the area. This area will be called block 2.

The data divided into blocks by the area dividing circuit 2 is supplied to the ADRC circuit 3 and the delay circuit 8. The delay circuit 8 delays the data for the time required for the processing of the ADRC circuit 3, the class code generation circuit 6, and the ROM table 7, and outputs the delayed data to the estimation calculation circuit 9.

The ADRC circuit 3 is supplied with S for each area.
A pattern of one-dimensional or two-dimensional level distribution of D data is detected, and the data of each area is converted from 8-bit SD data to 2-bit SD as described above.
Pattern compression data is formed by performing an operation for compressing the data, and the pattern compression data is supplied to the class code generating circuit 6.

Originally, ADRC (Adaptive Dynamic Range)
Coding) is an adaptive requantization method developed for high-efficiency coding for VTR (Video Tape Recoder). However, since the local pattern of the signal level can be efficiently expressed with a short word length, the present invention In this embodiment, it is used for code generation for classifying signal patterns. The ADRC circuit uses the following equation (1) to set the maximum value MA in the area, where DR is the dynamic range in the area, n is the bit allocation, L is the data level of the pixels in the area, and Q is the requantization code.
The region between X and the minimum value MIN is equally divided by the designated bit length and requantization is performed.

DR = MAX-MIN + 1 Q = {(L-MIN + 0.5) × 2 / DR} (1) However, {} means a truncation process.

In this embodiment, it is assumed that SD data of 6 pixels divided by the area dividing circuit 2 is compressed into 2 bits. Let the compressed SD data be q _{1 to} q ₆ , respectively.

On the other hand, the SD image signal supplied from the input terminal 1 is also supplied to the area dividing circuit 4. The area dividing circuit 4 also divides the supplied SD image signal into a plurality of areas. In this embodiment, from the supplied SD image signal, SD pixels of, for example, upper and lower 3 pixels in the previous frame of HD pixels to be created are divided into areas of 1 pixel × 6 lines, totaling 6 pixels, and created. In the same frame as the HD pixel to be processed, for example, upper and lower three SD pixels are divided into regions each including 1 pixel × 6 lines and a total of 6 pixels.

That is, for mode 1, SD pixels m ₁ to m of the previous frame for HD pixel y ₁ in FIG.
m ₆ and SD pixels n _{1 to} n _{6 of the} same frame correspond to the area. Regarding mode 2, HD in FIG.
The SD pixels m _{1 to} m _{6 in} the previous frame and the SD pixels n _{1 to} n _{6 in the} same frame for the pixel y ₁ correspond to the area.

The data cut out by the area dividing circuit 4 is supplied to the motion class determining circuit 5. The motion class determination circuit 5 calculates the difference of the SD data supplied for each area, and the absolute value processing is performed on the calculated difference. The average value param of the SD data subjected to the absolute value processing is calculated, and the threshold value processing is performed on the average value param to calculate the motion parameter that is the motion index, and the calculated motion parameter From movement class mv-c
The lass is decided. The determined motion class mv-class is
It is supplied to the class code generation circuit 6. Specifically, the motion class determination circuit 5 calculates the average value param of the absolute values of the differences of the supplied SD data by the following equation (2).

[0037]

[Equation 1] However, in this embodiment, n = 6.

The average value param of the absolute values of the SD data differences calculated by the above method is set to a preset threshold value, and the average value param of the absolute values of the SD data differences is used to calculate the motion class mv-class. Is determined. For example, in this embodiment, four motion classes mv-class are provided, and the average value param and the motion class mv-class are set as shown in FIG.

In the class code generation circuit 6, the following equation (3) is calculated based on the parameter compression data supplied from the ADRC circuit 3 and the motion class mv-class supplied from the motion class determination circuit 5. By
The class to which the block belongs is detected, and the class code class indicating the class is supplied to the ROM table 7. This class code class indicates a read address from the ROM table 7.

[0040]

[Equation 2] In this example, n is 6 and P is 2.

In the ROM table 7, coefficient data for calculating HD data corresponding to SD data is learned for each class by using a linear estimation formula by learning the relationship between SD data patterns and HD data. Remembered
This is information for converting SD data into HD data which is image information having a higher resolution than this image information, that is, HD data which conforms to the so-called high-definition system standard by the linear estimation formula. In this embodiment, the coefficient data is prepared independently for mode 1 and mode 2. The method of creating the coefficient data stored in the ROM table 7 will be described later. From ROM table 7, class code cl
From the address indicated by ass, w _i (class) which is the coefficient data of the class is read. This coefficient data is supplied to the estimation calculation circuit 9.

In the estimation operation circuit 9, SD data supplied from the area dividing circuit 2 and coefficient data w supplied from the ROM table 7 via the delay circuit 8.
HD data corresponding to the input SD data is calculated based on _i (class).

More specifically, the estimation calculation circuit 9 uses the SD data supplied from the delay circuit 8 and the coefficient data supplied from the ROM table 7, and uses the coefficient data for the block 1 for the mode 1. For mode 2, the coefficient data of block 2 is used to generate coefficient data w
_The HD data corresponding to the input SD data is calculated by performing the calculation shown in the following Expression (4) based on _i (class). The created HD data is supplied to the horizontal interpolation filter 10.

Hd ′ = w ₁ x ₁ + w ₂ x ₂ + w ₃ x ₃ + w ₄ x ₄ + w ₅ x ₅ + w ₆ x ₆ (4)

The horizontal interpolation filter 10 is the same as the horizontal interpolation filter 42 of FIG. 9, and the number of pixels in the horizontal direction is doubled by the interpolation processing. Horizontal interpolation filter 1
The output of 0 is output via the output terminal 11. HD data output via the output terminal 11 is, for example, H
It is supplied to a television receiver for D, a video tape recorder device for HD, and the like.

As described above, the coefficient data for estimating the HD data corresponding to the SD data is obtained for each class in advance by learning and then stored in the ROM table 7, and the inputted SD data, And ROM table 7
Calculation is performed based on the coefficient data read from
By forming and outputting HD data corresponding to the input SD data, it is possible to output data closer to the actual HD data, unlike the case where the input SD data is simply interpolated.

Next, a method of creating (learning) the coefficient data stored in the ROM table 7 will be described with reference to FIG. In order to obtain coefficient data by learning, first,
1 / HD image that corresponds to the already known HD image
An SD image with 4 pixels is formed. Specifically, by the ideal filter circuit shown in FIG. 8, vertical pixels of the HD data supplied through the input terminal 21 have the vertical frequency in the field reduced to 1 / by the vertical thinning filter 22.
The horizontal thinning filter 23 thins out the pixels in the horizontal direction of the HD data to obtain SD data. The SD data obtained by the vertical thinning filter 23 is supplied to the area dividing circuit 24.

The area dividing circuit 24 divides the SD image signal supplied from the horizontal thinning filter 23 into a plurality of areas. Specifically, the area dividing circuit 24 has the same function as the area dividing circuit 2 described above.
In this embodiment, like the area dividing circuit 2, the area is divided into areas each having 6 pixels. That is, for mode 1, the area of the block 1 is divided, and for mode 2, the area of the block 2 is divided. SD for each area
The data is supplied to the ADRC circuit 25 and the normal equation adding circuit 29.

The ADRC circuit 25 detects a one-dimensional or two-dimensional level distribution pattern of the SD data supplied for each area, and as described above, all or part of the data in each area. Pattern compression data is formed by performing an operation of compressing the data of 8 to SD data of 2 bits, for example, and the pattern compression data is supplied to the class code generating circuit 28. The ADRC circuit 25 is the same as the ADRC circuit 3 described above. In this embodiment, SD data (SD pixel x in FIG. 3 and FIG. 4) of each area composed of 6 pixels divided by the area dividing circuit 24 is used.
_{1 to} x ₆ ) are subjected to ADRC and compressed to 2 bits each.

On the other hand, the SD pixel signal supplied from the horizontal thinning filter 23 is also supplied to the area dividing circuit 26. Specifically, the area dividing circuit 26 has the same function as the area dividing circuit 4 described above. The SD data cut out by the area dividing circuit 26 is supplied to the motion class determining circuit 27. Specifically, the motion class determination circuit 27 performs the same motion as the motion class determination circuit 5 described above. The motion class mv-class determined by the motion class determination circuit 27 is supplied to the class code generation circuit 28.

The class code generation circuit 28 is the same as the class code generation circuit 6 described above,
The compressed pattern data supplied from the C circuit 25 and the motion class mv-c supplied from the motion class determination circuit 27.
The class to which the block belongs is detected by performing the operation of Expression (2) based on lass, and the class code indicating the class is output. The class code generation circuit 28 outputs the class code to the normal equation addition circuit 29.

Here, in order to explain the normal equation adding circuit 29, learning of a conversion formula from a plurality of SD pixels to HD pixels and signal conversion using the prediction formula will be described. For the sake of explanation, a case will be described below where learning is generalized and prediction is performed using n pixels. X ₁ The SD pixel level, respectively, ‥‥, as x _n, p-bit AD respectively
The requantized data obtained as a result of RC is q ₁ , ..., Q _n
And

At this time, the class code class of this area
Is defined by equation (2). As described above, the SD pixel level is set to x ₁ , ..., X _n , and the HD pixel level is set to y.
Then, an n-tap linear estimation formula based on the coefficient data w ₁ , ..., W _n is set for each class. Equation (5)
Shown in Before learning, w _i is an undetermined coefficient.

Y = w ₁ x ₁ + w ₂ x ₂ + ... + w _n x _n (5)

Learning is performed on a plurality of signal data for each class. When the number of data is m, the following equation (6) is set according to the equation (5).

Y _k = w ₁ x _k1 + w ₂ x _k2 + ... + w _n x _kn (6) (k = 1, 2, ... M)

When m> n, coefficient data w _i , ... W _n
Is not uniquely determined, the element of the error vector e is defined by the following equation (7), and coefficient data that minimizes the equation (8) is obtained. This is the so-called least squares method.

E _k = y _k − {w ₁ x _k1 + w ₂ x _k2 + ... + w _n x _kn } (7) (k = 1, 2, ... M)

[0059]

(Equation 3)

Here, the partial differential coefficient by w _{i in} equation (8) is obtained. That is, each w _i may be obtained so that the following expression (9) is set to “0”.

[0061]

[Equation 4]

When X _ij and Y _i are defined as in equations (10) and (11) below, equation (9) can be rewritten into equation (12) using a matrix.

[0063]

(Equation 5)

[0064]

(Equation 6)

[0065]

(Equation 7)

This equation is generally called a normal equation. The normal equation adding circuit 29 includes a class code class supplied from the class code generating circuit 28, SD pixels x ₁ , ..., X _n supplied from the area dividing circuit 24.
H corresponding to SD data supplied from the input terminal 21
This normal equation is added using D pixel y.

After the input of all the learning data, the normal equation addition circuit 29 determines the prediction coefficient determination circuit 30.
Output normal equation data to. Prediction coefficient determination circuit 30
Solves w _i using a general matrix solution method such as a sweeping method of a normal equation and calculates a prediction coefficient. The prediction coefficient determination circuit 30 writes the calculated prediction coefficient in the memory 31.

As a result of learning as described above, the memory 3
1 stores a prediction coefficient for estimating the HD pixel of interest y for each pattern defined by the quantized data q ₁ , ..., Q ₆ , which is statistically closest to the true value. . The table stored in the memory 31 is the ROM table 7 used in the image signal converting apparatus of the present invention as described above. Through the above processing, learning of coefficient data for creating HD data from SD data is completed by the linear estimation formula.

In the description of this embodiment, ADRC is provided as the information compressing means, but this is just an example, and any information compressing means capable of expressing the pattern of the signal waveform with a small number of classes. What is provided is arbitrary, and for example, compression means such as DPCM (predictive coding) or VQ (vector quantization) may be used.

Furthermore, in the description of this embodiment, for the sake of simplicity, the horizontal interpolation filter 10 is used for horizontal up-conversion, but instead, a ROM for horizontal up-conversion is prepared and the horizontal up-conversion is performed. It is of course possible to adopt the present invention using an estimation formula also in conversion.

Further, in the description of this embodiment, the pattern of the signal waveform is divided into one dimension and expressed by the area dividing circuit 4, but it may be divided into two dimensions.

Further, in the description of this embodiment, the motion class mv-c is calculated by using the SD image data which is one-dimensionally divided by the area dividing circuit 5 and the motion class determining circuit 6.
Although the lass is determined, the area division may be two-dimensional division. Rather, it is preferable to make it two-dimensional. Further, for simplicity, this time, the area division by the area division circuit 4 and the area division by the area division circuit 5 are similar area divisions, but they are originally completely different, and similar area divisions are performed. There is no need to do it.

Furthermore, in the description of this embodiment, the SD pixel used for class classification and the SD pixel used in the linear estimation formula are the same, but they do not necessarily have to be the same. When different pixels are used, it is desirable that the SD pixels used in the class classification be included in the SD pixels used in the linear estimation formula, and the SD pixels used in the linear estimation formula additionally used are: HD to estimate
It is desirable to use only those belonging to the same field as the pixel.

[0074]

EFFECTS OF THE INVENTION In the estimation method by classifying the spatiotemporal structure of the conventionally proposed method, a failure may occur in an estimated image due to a motion mismatch. This method has a drawback that the number of classes is significantly increased in order to reduce the problem, but according to the method of the present invention, while suppressing an increase in the number of classes,
The deterioration can be greatly reduced.

[Brief description of drawings]

FIG. 1 is a block diagram of an embodiment of an image information conversion apparatus according to the present invention.

FIG. 2 is a schematic diagram for explaining the positional relationship between SD data and HD data.

FIG. 3 is a schematic diagram for explaining data used for class division.

FIG. 4 is a schematic diagram for explaining data used for class division.

FIG. 5 is a schematic diagram for explaining data used for determining a motion class.

FIG. 6 is a schematic diagram for explaining data used for determining a motion class.

FIG. 7 is a schematic diagram illustrating an example relationship between an average value param and a motion class.

FIG. 8 is a schematic diagram for explaining a case of creating a correction data table.

FIG. 9 is a block diagram of a conventional image information conversion device.

FIG. 10 is a circuit diagram of a main part of a conventional image information conversion device.

FIG. 11 is a schematic diagram for explaining a problem of a conventional space-time class division method.

FIG. 12 is a schematic diagram for explaining a problem of the conventional space-time class division method.

FIG. 13 is a schematic diagram for explaining problems of the conventional space-time class division method.

[Explanation of symbols]

 2, 4 Region division circuit 3 ADRC circuit 5 Motion class determination circuit 6 Class code generation circuit 7 ROM table 8 Delay circuit 9 Estimating arithmetic circuit 10 Horizontal interpolation filter

Claims (3)

[Claims] 1. An image information conversion device adapted to convert a digital image signal into a digital image signal having a larger number of pixels, wherein image information supplied from the outside is divided into a plurality of blocks of data within the same frame. A pattern of level distribution is detected for each block divided by the first image information dividing unit and the first image information dividing unit, and a class belonging to each block is determined based on the detected pattern. As a result, class detection means for outputting class detection information, and second image information division means for dividing the above-mentioned image information supplied from the outside into a plurality of blocks composed of a plurality of interframe data at the same spatial position The average value of the absolute values of the inter-frame differences is calculated for each block divided by the second image information dividing means, and is set in advance. Based on the determined threshold value, the class representing the motion is determined to output the motion class detection information, and the information of the class detection means and the motion class detection means is integrated to finally determine Class code generating means for determining a class, and coefficient data of an estimation formula, which is information for converting the image information supplied from the outside into image information having a higher resolution than the image information, is stored for each class. The coefficient information storing means for outputting the coefficient data according to the class from the class code generating means, and the image information supplied from the outside according to the coefficient data from the coefficient data storing means. An image information conversion apparatus comprising: an image conversion unit that converts the image information into image information having a higher resolution than the image information and outputs the image information. 2. The image information conversion apparatus according to claim 1, wherein the image information supplied from the outside in the first image information dividing means is used in a first mode and / or a second mode. In the first mode dividing means for dividing into blocks and the second image information dividing means, the image information supplied from the outside is divided into a first mode and / or a range larger than the first mode dividing means. , A second mode dividing means for dividing into blocks of the second mode. 3. The image information conversion apparatus according to claim 1, wherein the coefficient data generating means has a memory means for storing the coefficient data for each class, and the spatial and / or time of the pixel of interest. When the value of the pixel of interest is created by linearly combining linearly combining the values of a plurality of pixels and the coefficient data, the error between the created value and the true value of the pixel of interest is minimized. An image information conversion device characterized in that the coefficient data for each class is obtained in advance by learning.