JP2000069433A - Image information converter, image information conversion method and television receiver - Google Patents

Abstract

PROBLEM TO BE SOLVED: To effectively use a bit width assigned in a memory to store a prediction coefficient used for image information conversion. SOLUTION: A class value generated by a class synthesis circuit 10 is fed to a coefficient memory 11 and a weight amount memory 12. The coefficient memory 11 stores prediction coefficient data resulting from being rounded so as to fall within a prescribed data width. Then the memory 11 gives prediction coefficient data designated by the class value to an estimate prediction arithmetic circuit 4. The estimate prediction arithmetic circuit 4 applies arithmetic processing for generating prediction data to the data and gives the prediction generating data to a bit shift processing circuit 5. The bit shift processing circuit 5 applies bit shift processing equivalent to an arithmetic processing of multiplying 2n by each pixel value according to received weight amount data. According to the processing above, rounding processing conducted in the case of generating the prediction coefficient data is compensated and line data y1, y2 are properly generated.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] 1. Field of the Invention [0002] The present invention relates to an image information conversion device, an image information conversion method, and a television receiver having a function of generating an image signal having a higher resolution from an input image signal.

[0002]

2. Description of the Related Art For the purpose of obtaining an image signal having a higher resolution than an input image signal, image information conversion processing for forming an output image signal having a scanning line structure different from that of the input image signal is performed. As image information conversion processing, class division is performed according to the three-dimensional (spatio-temporal) distribution of the signal level of the input image signal,
A class classification adaptive process for predicting and generating pixels with reference to a class value obtained thereby has been proposed.

[0003] The calculation processing related to prediction generation is performed using prediction coefficients determined by a predetermined calculation for each class. Therefore, it is necessary to store prediction coefficient data for expressing prediction coefficients in a memory in the apparatus. In general, a bit width capable of expressing the maximum value of a prediction coefficient is used as a bit width assigned to each prediction coefficient in such a memory. However, when the value of the prediction coefficient fluctuates greatly, there is a problem that a part of the allocated bit width that is not used effectively increases.

[0004]

SUMMARY OF THE INVENTION Accordingly, an object of the present invention is to effectively use the bit width allocated in the memory corresponding to each prediction coefficient even when the value of the prediction coefficient fluctuates greatly. It is an object of the present invention to provide an image information conversion device, an image information conversion method, and a television receiver which enable the above.

[0005]

According to a first aspect of the present invention, there is provided an image information converting apparatus for forming an output image signal having a different scanning line structure from an input image signal. A first image data selecting unit that selects a neighboring pixel having a relationship from the input image signal, and an image data selected by the first image data selecting unit.
A space class detecting means for detecting a pattern of the level distribution and determining a space class value indicating a space class to which the point of interest belongs based on the detected pattern; A second image data selecting means for selecting neighboring pixels having the following positional relationship, a first storing means for storing prediction coefficient data predetermined for each space class, and a prediction stored in the first storing means. Second storage means for storing weight data for the coefficient data for each space class, prediction coefficient data selected from the first storage means in accordance with the space class value, and weight selected from the second storage means Arithmetic processing means for performing arithmetic processing for estimating an output image signal based on image data obtained by the second image data selecting means using the amount data A picture information converting apparatus according to claim.

According to a second aspect of the present invention, there is provided an image information conversion apparatus for forming an output image signal having a different scanning line structure from an input image signal, wherein adjacent pixels having a predetermined positional relationship with respect to a predetermined point of interest are determined. A level distribution pattern is detected from first image data selection means selected from the input image signal, and image data selected by the first image data selection means, and a space to which a point of interest belongs based on the detected pattern. Space class detection means for determining a space class value indicating a class; and second image data for selecting, from an input image signal, neighboring pixels having a predetermined positional relationship with a point of interest in a plurality of frames in the input image signal Calculating a sum of absolute differences between frames from the image data selected by the selection means and the second image data selection means; A motion class detecting means for determining a motion class value; a class synthesizing means for synthesizing a space class value and a motion class value to generate a class value; Third image data selection means for selecting neighboring pixels having a predetermined positional relationship;
First storage means for storing prediction coefficient data predetermined for each space class, and second storage means for storing weight data for the prediction coefficient data stored in the first storage means for each space class And using the prediction coefficient data selected from the first storage means and the weight data selected from the second storage means in accordance with the class value to obtain the image data obtained by the third image data selection means. And an arithmetic processing unit for performing an arithmetic process for estimating an output image signal based on the output image signal.

According to a sixth aspect of the present invention, there is provided an image information conversion method for forming an output image signal having a different scanning line structure from an input image signal, wherein adjacent pixels having a predetermined positional relationship with respect to a predetermined target point are determined. A first image data selecting step for selecting from the input image signal, and a level distribution pattern detected from the image data selected in the first image data selecting step, and a space to which a point of interest belongs based on the detected pattern. A space class detecting step of determining a space class value indicating a class; a second image data selecting step of selecting a neighboring pixel including a point of interest from the input image signal and having a predetermined positional relationship with the point of interest; A first storing step of storing prediction coefficient data determined in advance for each space class, and a method for storing prediction coefficient data stored in the first storage step. The weight amount data, a second storage step of storing each spatial class, according to the spatial class value,
Prediction coefficient data selected from the first storage step;
An arithmetic processing step of performing an arithmetic processing for estimating an output image signal based on the image data obtained in the third image data selecting step, using the weight amount data selected from the second storage step. An image information conversion method characterized by having

According to a seventh aspect of the present invention, there is provided an image information conversion method for forming an output image signal having a different scanning line structure from an input image signal, wherein adjacent pixels having a predetermined positional relationship with respect to a predetermined target point are determined. A first image data selecting step for selecting from the input image signal, and a level distribution pattern detected from the image data selected in the first image data selecting step, and a space to which a point of interest belongs based on the detected pattern. A space class detection step of determining a space class value indicating a class; and second image data for selecting, from the input image signal, neighboring pixels having a predetermined positional relationship with a point of interest in a plurality of frames in the input image signal. Calculating a sum of absolute differences between frames from the image data selected in the selecting step and the second image data selecting step; A motion class detecting step of determining a motion class value representing a motion based on the result, a class synthesizing step of synthesizing a spatial class value and a motion class value to generate a first class value, A third image data selecting step of selecting neighboring pixels including a point and having a predetermined positional relationship with respect to the point of interest, a first storing step of storing prediction coefficient data predetermined for each space class, A second storage step of storing weight data for the prediction coefficient data stored in the first storage step for each space class;
Prediction coefficient data selected from the storage step
And an arithmetic processing step of performing an arithmetic processing for estimating an output image signal based on the image data obtained in the second image data selecting step using the weight amount data selected from the storing step. Is a method for converting image information.

[0011] According to an eleventh aspect of the present invention, in a television signal receiver in which an output image signal having a different scanning line structure is formed from an input image signal, neighboring pixels having a predetermined positional relationship with respect to a predetermined point of interest are provided. , A level distribution pattern is detected from first image data selecting means for selecting from the input image signal, and image data selected by the first image data selecting means, and the point of interest belongs based on the detected pattern. Space class detection means for determining a space class value indicating a space class; and second image data selection means for selecting, from an input image signal, neighboring pixels that include a point of interest and have a predetermined positional relationship with the point of interest. First storage means for storing prediction coefficient data predetermined for each space class, and weight data for the prediction coefficient data stored in the first storage means. The second storage means for storing for each space class, the prediction coefficient data selected from the first storage means and the weight data selected from the second storage means according to the space class value, And a calculation processing means for performing calculation processing for estimating an output image signal based on the image data obtained by the second image data selection means.

According to a twelfth aspect of the present invention, in a television signal receiver in which output image signals having different scanning line structures are formed from input image signals, neighboring pixels having a predetermined positional relationship with respect to a predetermined point of interest. , A level distribution pattern is detected from first image data selecting means for selecting from the input image signal, and image data selected by the first image data selecting means, and the point of interest belongs based on the detected pattern. A space class detecting means for determining a space class value indicating a space class; and a second image for selecting, from the input image signal, neighboring pixels having a predetermined positional relationship with a point of interest in a plurality of frames in the input image signal. Calculating the sum of the inter-frame difference absolute values from the image data selected by the data selection means and the second image data selection means;
A motion class detecting unit that determines a motion class value representing a motion based on the calculation result; a class synthesizing unit that generates a class value by synthesizing the spatial class value and the motion class value; A third image data selecting means for selecting neighboring pixels having a predetermined positional relationship with respect to the point of interest, a first storing means for storing prediction coefficient data predetermined for each space class, The second storage means for storing the weight amount data for the prediction coefficient data stored in the storage means for each spatial class, and the class value,
Prediction coefficient data selected from the first storage means,
And arithmetic processing means for performing arithmetic processing for estimating an output image signal based on image data obtained by the third image data selecting means, using the weight amount data selected from the storage means. A television signal receiver characterized by the following.

According to the invention described above, the coefficient data generated as a result of the processing (rounding processing) for storing the information representing the prediction coefficient in a predetermined bit width is related to the weight data. Thus, arithmetic processing for prediction generation can be performed.

Therefore, even when the value of the prediction coefficient greatly changes depending on the class, it is not necessary to increase the bit width allocated to each coefficient data in the coefficient memory for storing the coefficient data.

[0013]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Prior to the description of an embodiment of the present invention, a description will be given of an image information conversion process as a premise thereof. This process converts a standard resolution digital image signal (hereinafter, referred to as an SD signal) into a high resolution image signal (which may be referred to as an HD signal) and outputs the same. As the SD signal at this time, for example, an interlaced image signal (hereinafter referred to as a 525i signal) having 525 lines is used. As a high-resolution image signal, for example, if the number of lines is 5
25 progressive video output signals (hereinafter, 5
25p signal) is used. Further, the number of pixels in the horizontal direction in the output image signal is twice the number of pixels in the horizontal direction in the input image signal.

In the image information conversion processing, the resolution is enhanced by the classification adaptive processing proposed by the present applicant. The classification adaptive processing is different from the one that forms a high-resolution signal by the conventional interpolation processing. That is, in the class classification adaptive processing, class division is performed according to the three-dimensional (spatio-temporal) distribution of the signal level of the input SD signal, and the prediction count value obtained by learning in advance for each class is stored in a predetermined storage unit. This is a process of outputting an optimum estimated value by an operation based on a prediction formula. Through the classification adaptive processing, it is possible to obtain a resolution higher than the resolution of the input SD signal.

The image signal obtained by such processing will be described in more detail. FIG. 1 shows an example of the arrangement of pixels in an image information conversion process for converting a 525i signal as an input SD signal into a 525p signal as an output image signal by enlarging a part of an image of one field. . Here, a large dot indicates a pixel of the 525i signal, and a small dot indicates a pixel of the 525p signal.

Line data y1 (shown as small black dots) at the same position as the line of the 525i signal and line data y2 (shown as small white dots) at an intermediate position between the upper and lower lines of the 525i signal are shown. The 525p signal is predicted and generated by being formed. FIG. 1 shows a pixel arrangement in an odd field of a certain frame. In other fields (even fields), each line of the 525i signal and the 525p signal is spatially shifted by 0.5 line.

From the input SD signal, line data y1, y
FIG. 2 shows an example of an arrangement of SD pixels (hereinafter, referred to as space class taps) necessary to detect a space class for No. 2. In FIG. 2, when time progresses in the horizontal direction (left to right), pixels in each field are shown arranged in the vertical direction.

The fields shown are denoted as F-1 / o, F-1 / e, F / o, and F / e in order from the left.
Note that F-1 / o is a notation indicating that it is "a field including the odd-numbered (odd) -th scanning line of the (F-1) -th frame". Similarly, F-1 / e means "a field consisting of even-numbered (even) -th scanning lines of the (F-1) -th frame", and F / o means "an odd-numbered scanning line of the F-th frame." F / e means “a field consisting of even-numbered scanning lines of the F-th frame”.

In one example, the field F / o
Are used as space class taps for the line data y1 in the field F-1 / e, and T1, T2, and T3 in the field F / o are all five pixel values. However, the arrangement of the space class taps is not limited to this. For example, a plurality of input pixels in the horizontal direction may be used as space class taps.

FIG. 3 shows an example of a general configuration for performing the above-described image information conversion processing. The following description is
A processing system for converting a 525i signal as an input SD signal into a 525p signal as an output image signal will be described as an example. However, image information conversion processing between an input SD signal / output image signal having another image signal format can be performed by a similar configuration. The input SD signal (525i signal) is supplied to the tap selection circuits 1, 6, and 7.

The tap selection circuit 1 includes line data y1,
Calculation processing for predicting and estimating y2 (formula (1) described later)
Area including a plurality of pixels required for the calculation processing according to
SD pixels necessary for predicting and estimating 1, y2 (hereinafter, referred to as
(Referred to as prediction tap). The selected prediction tap is supplied to the estimated prediction calculation circuit 4. Here, as the prediction tap, the same as a space class tap described later can be used. However, in order to improve the prediction accuracy, the selection is made based on the prediction tap position information corresponding to the class.

Further, a prediction coefficient necessary for predicting and estimating the line data y1 and y2 is supplied from the coefficient memory 11 to be described later to the estimation prediction operation circuit 4. Based on the prediction taps supplied from the tap selection circuit 1 and the prediction coefficients supplied from the coefficient memory 11, the estimation prediction calculation circuits 4 and 5 sequentially predictively generate pixel values y according to the following equation (1).

Y = w ₁ × x ₁ + w ₂ × x ₂ + ‥‥ + w _n × x _n (1) where x ₁ , ‥‥, x _n are each prediction tap,
w ₁ , ‥‥, and w _n are respective prediction coefficients. That is, Expression (1) is an expression for predictively generating a pixel value y using n prediction taps. Line data y1 and y2 are predicted and generated as a column of pixel values y.

The estimation / prediction calculation circuit 4 calculates the line data y
1 and y2 are supplied to the line order conversion circuit 5. The line order conversion circuit 5 performs a line double speed process on the supplied line data to generate a high-resolution signal. This high resolution signal is used as a final output image signal. Although not shown, an output image signal is supplied to a CRT display. The synchronization system of the CRT display is configured so that an output image signal (525p signal) can be displayed. Also,
As the input SD signal, a broadcast signal or a playback signal of a playback device such as a VTR is supplied. That is, this embodiment can be incorporated in a television receiver or the like.

On the other hand, the tap selection circuit 6 selects a space class tap from the input SD signal. The output of the tap selection circuit 6 is supplied to the space class detection circuit 8. Further, the tap selection circuit 7 selects an SD pixel (hereinafter, referred to as a motion class tap) necessary for detecting a motion class from the input SD signal. The output of the tap selection circuit 7 is supplied to the motion class detection circuit 9.

The space class detection circuit 8 detects a space class value based on the supplied space class tap, and supplies the detected space class value to the class synthesis circuit 10. The motion class detection circuit 9 detects a motion class value based on the supplied motion class tap, and supplies the detected space class value to the class synthesis circuit 10.

The class synthesizing circuit 10 synthesizes the space class value and the motion class value, and supplies the synthesized class value to the coefficient memory 11. The coefficient memory 11 stores a prediction coefficient predetermined by learning described later. Then, the prediction coefficient data specified by the synthesized class value supplied from the class synthesis circuit 10 is output to the estimated prediction calculation circuit 4. In order to perform such an output, a method of storing prediction coefficient data in the coefficient memory 11 along an address specified by the synthesized class information may be used.

Here, the space class detection will be described in more detail. In general, a space class detection circuit detects a spatial pattern of a level distribution of image data based on a level distribution pattern of a space class tap, and generates a space class value based on the detected spatial pattern. In this case, in order to prevent the number of classes from becoming enormous, a process of compressing 8-bit input pixel data into data of a smaller number of bits is performed for each pixel. As an example of such information compression processing, ADRC (Adaptive Dynamic Ra
nge Coding) can be used. Further, DPCM (predictive coding), VQ (vector quantization), or the like can be used as the information compression processing.

ADRC is originally designed for VTR (Video Tape Re
coder) is an adaptive requantization method developed for high-efficiency coding. However, since a local pattern of a signal level can be efficiently represented by a short word length, this form of ADRC
Is used to generate codes for spatial class classification. ADR
C is the dynamic range of the spatial class tap DR,
Assuming that the bit allocation is n, the data level of the pixel of the space class tap is L, and the requantization code is Q, the maximum value MAX and the minimum value MIN are equalized by the specified bit length by the following equation (2). And requantization is performed.

DR = MAX−MIN + 1 Q = {(L−MIN + 0.5) × 2 / DR} (2) where {} indicates a truncation process.

Next, the motion class detection will be described in more detail. The motion class detection circuit 21 calculates an average value param of the inter-frame difference absolute value based on the supplied motion class tap according to the following equation (3). Then, a motion class value is detected based on the calculated param value.

[0032]

(Equation 1)

In equation (3), n is the number of motion class taps, and can be set to, for example, n = 6. Then, by comparing the value of param with a preset threshold value, a motion class value that is a motion index is determined. For example, the motion class value is 0 when param ≦ 2, the motion class value is 1 when 2 <param ≦ 4, and the motion class value is 2 when p <param ≦ 8.
When aram> 8, a motion class value such as motion class value 3 is generated. The motion class value 0 indicates that the motion is the minimum (still), and the motion class values 1, 2, and 3 are determined to be large as the motion becomes. Note that a motion vector may be detected, and a motion class may be detected based on the detected motion vector.

Next, the processing related to the generation of prediction coefficients will be described. FIG. 4 shows an example of the configuration of the prediction coefficient generation processing system. A known signal (for example, a 525p signal) having the same signal format as the output image signal is supplied to the thinning filter 20 and the normal equation adding circuit 27. The thinning filter 51 has one pixel in each of the horizontal direction and the vertical direction.
/ 2, and generates an SD signal (for example, a 525i signal) having 1/4 the number of pixels of the signal supplied as a whole.

As such processing, for example, pixels are decimated by a vertical decimating filter so that the vertical frequency of the input image signal becomes １ ／, and horizontal decimating such that the horizontal frequency becomes ２. Processing such as thinning out pixels is performed by the filter. The SD signal generated by the thinning filter 51 is output to the tap selection circuits 21 and 2.
2, 23. By changing the characteristics of the decimation filter 20, the characteristics of the learning can be changed, and thereby the image quality of the image obtained by the conversion can be controlled.

The tap selection circuit 21 selects a prediction tap and supplies the selected prediction tap to the normal equation adding circuit 27. Further, the tap selection circuit 22 selects a prediction tap, and supplies the selected prediction tap to the space class detection circuit 24. On the other hand, the tap selection circuit 23 selects a prediction tap, and uses the selected prediction tap as a motion class detection circuit 25.
To supply.

The space class detection circuit 24 detects a space class value based on the supplied space class tap, and supplies the detected space class value to the class synthesis circuit 26. Further, the motion class detection circuit 24 detects a motion class value based on the supplied motion class tap, and supplies the detected motion class value to the class synthesis circuit 26. The class combining circuit 26 combines the supplied space class value and motion class value, and combines the combined class value with the normal equation adding circuit 2.
7

The normal equation addition circuit 27 calculates data used in a calculation process for solving a normal equation using the prediction coefficient as a solution. That is, the normal equation adding circuit 27
Is a normal equation in which a prediction coefficient used for prediction generation of line data y1 and y2 is solved by performing an addition process based on the input SD signal, the output of the tap selection circuit 21 and the output of the class synthesis circuit 26. Calculate the data required to solve

The data calculated by the normal equation addition circuit 27 is supplied to a prediction coefficient determination circuit 28. The prediction coefficient determination circuit 28 performs a calculation process for solving a normal equation based on the supplied data, and calculates a prediction coefficient used for generating a prediction of the line data y1 and y2. The calculated prediction coefficients are supplied to the coefficient memory 29 and stored.

Here, the normal equation will be described. As described above, using n prediction taps, each pixel forming the line data y1 and y2 is sequentially predicted and generated by the above-described equation (1). In Equation (1), before learning, the prediction coefficients w ₁ , ‥‥, and w _n are undetermined coefficients. The learning is performed on a plurality of input image signal data for each class. When the total number of the input image signal data is expressed as m, the following equation (4) is set according to the equation (1).

Y _k = w ₁ × x _k1 + w ₂ × x _k2 + ‥‥ + w _n × x _kn (4) (k = 1,2, ‥‥, m) When m> n, the prediction coefficients w ₁ , Since ‥‥ and w _n are not uniquely determined, the element e _k of the error vector e is defined by the following equation (5), and the prediction coefficient is set so as to minimize the error vector e defined by the equation (6). To be determined. That is, the prediction coefficient is uniquely determined by the so-called least square method.

E _k = y _k − {w ₁ × x _k1 + w ₂ × x _k2 + Δ + w _n × x _kn } (5) (k = 1, 2, Δm)

[0043]

(Equation 2)

As a practical calculation method for obtaining the prediction coefficient minimizing e ² in equation (6), partial differentiation of e ² with the prediction coefficient w _i (i = 1,2 ‥‥) (7)) It is sufficient to determine each prediction coefficient w _i so that the partial differential value becomes 0 for each value of _i .

[0045]

(Equation 3)

A specific procedure for determining each prediction coefficient w _i from equation (7) will be described. If X _ji and Y _i are defined as in equations (8) and (9), equation (7) can be written in the form of a determinant of equation (10).

[0047]

(Equation 4)

[0048]

(Equation 5)

[0049]

(Equation 6)

Equation (10) is generally called a normal equation. Based on the class information supplied from the class synthesis circuit 26, the prediction taps supplied from the prediction tap selection circuit 21, and the input image signal, the normal equation addition circuit 27 performs normal equation data, that is, equation (8).
The values of X _ji and Y _i according to (9) are calculated. Then, the calculated normal equation data is supplied to the prediction coefficient determination unit 28. Prediction coefficient determining unit 28, based on the normal equation data, performs calculation processing for solving the normal equation to calculate the prediction coefficient w _i in accordance with the general matrix solution such as a sweeping-out method.

In the general image information conversion processing as described above, the value of the prediction coefficient changes greatly. For this reason,
In order to store the prediction coefficients in the coefficient memory 11, the following method has been used. That is, the maximum value of the absolute value of the prediction coefficient is obtained, and a bit width capable of expressing the obtained maximum value is assigned as a bit width for storing each prediction coefficient value.

The bit width allocated in this way is:
It may not be used effectively for the following reasons. In general, when class detection is properly performed, the sum of prediction coefficients used for prediction generation of a specific class is substantially 1, and the value of each prediction coefficient does not become significantly larger than 1. . Further, when the value of the prediction coefficient fluctuates greatly, it is often difficult to accurately estimate the output image signal from the input image signal, and a class that requires such a prediction coefficient for prediction generation is detected. The ratio is usually very small compared to the total number of pixels in the input image signal.

Even in such a situation, when the bit width allocated to each prediction coefficient is determined based on the maximum value of the absolute values of all the prediction coefficients as described above, the bit width occupied in the input image signal is determined. The allocation of the bit width is governed by the class having a small ratio. For this reason,
For many classes, where the prediction factor is never much larger than one, the allocated bit width may not be used effectively.

Therefore, the present invention detects the maximum value of the prediction coefficient used for prediction generation for each class, generates a weight for each class in association with the detected maximum value, and fixes each prediction coefficient. The prediction coefficient data is generated by performing a rounding process to fit within the effective bit width. By storing the prediction coefficient data generated in this way, it is possible to effectively use the bit width assigned to each prediction coefficient in the memory. Then, by separately storing the weight amount for each class, and performing compensation corresponding to the rounding process using the weight amount, it is possible to accurately perform prediction generation.

Hereinafter, one embodiment of the present invention will be described with reference to the drawings as appropriate. One embodiment uses a 525i signal as an input SD signal and a 525i signal as an output image signal.
This is for performing image information conversion processing for converting into a 5p signal. However, the present invention can be applied to a case where conversion between an input SD signal and an output image signal having another image signal format is performed.

FIG. 5 shows an example of the configuration of a prediction coefficient generation processing system according to one embodiment. Here, the same components as those in the general prediction coefficient generation processing system described above with reference to FIG. The prediction coefficient generated by the prediction coefficient determination circuit 28 is supplied to the maximum value detection circuit 29. The maximum value detection circuit 29 performs the following processing for each class. First, the maximum value M of the absolute value of the prediction coefficient is detected, and the minimum power of 2 exceeding the detected maximum value M is obtained. That is, the value of ⁿ that satisfies 2 ^n-1 <M <2 ⁿ is obtained. The value of n is supplied to the weight memory 30 and the rounding circuit 31 as weight data for the class. The rounding circuit 31 stores the supplied weight amount data. Each prediction coefficient value is supplied to the rounding circuit 31 via the maximum value detection circuit 29.

The rounding circuit 31 performs a process of rounding the value of each supplied prediction coefficient for each class. First, using the supplied weight data n, an operation of dividing each prediction ^coefficient value by 2 ⁿ is performed. That is, each pixel value is bit-shifted to the left by the number of bits equal to the weight n. Further, in order to make the result of the division into a fixed effective bit width of, for example, 8 bits, processing such as truncating bits after the fixed effective bit width is performed. The prediction coefficient data obtained by the above rounding process is supplied to the coefficient memory 32. Note that a bit indicating information on the scale or the like may be added as necessary. As described above, for all classes, the prediction coefficient value is represented by the combination of the value contained in the fixed effective bit width and the weight amount data. The data stored in the coefficient memory 32 and the weight memory 30 are loaded into the coefficient memory 11 and the weight memory 12, respectively.

Next, a description will be given of an image information conversion process using the prediction coefficient values expressed as described above. FIG. 6 is a block diagram illustrating an example of a configuration of an image information conversion processing system according to an embodiment. Here, the same components as those in the general image information processing system described above with reference to FIG. The class value generated by the class synthesis circuit 10 is supplied to the coefficient memory 11 and also to the weight memory 12.

The coefficient memory 11 outputs prediction coefficient data specified by the supplied class value to the estimated prediction calculation circuit 4. Further, the weight memory 12 outputs the weight data specified by the supplied class value to the bit shift processing circuit 5. In order to perform such an output, a method of storing weight amount data in the weight amount memory 12 along an address specified by the class value may be used.

The estimated prediction operation circuit 4 supplies the line data value predicted and generated by performing the above-described operation processing to the bit shift processing circuit 5. The bit shift processing circuit 5 performs a bit shift process on the supplied line data value according to the supplied weight amount data.
That is, each pixel value is bit-shifted to the right by the number of bits equal to the weight n. The bit shift processing is an arithmetic processing for multiplying each pixel value by 2 ⁿ , and therefore, compensation corresponding to the rounding processing is performed on the line data value. It should be noted that processing based on bits indicating information on the scale and the like may be performed as necessary. With this processing, the line data y1 and y2 can be accurately generated.

In the above-described embodiment of the present invention, the arrangement of the space clasp is the same for y1 and y2. On the other hand, different spatial clasp arrangements may be used for y1 and y2 in consideration of the difference in the difficulty of predictive generation caused by the difference in the positional relationship between the input image signal and the scanning line. That is, it is generally more difficult to predict and generate line data y2 that is not at a position corresponding to the scan line of the input image signal than to predict and generate line data y1 at a position corresponding to the scan line of the input image signal. Considering, more space class taps may be arranged for y2. The present invention can be applied to such a case.

In one embodiment and another embodiment of the present invention, a 525i signal is converted into a 525p signal. However, the number of 525 lines is an example, and the number of 525 lines is other. This invention can also be applied to the present invention.
For example, an output image signal including a line including a number of pixels other than twice the number of pixels in the horizontal direction in the input SD signal may be predicted and generated. More specifically,
The present invention can be applied to a case where an image information conversion process for predicting and generating an interlace-type image signal with a 1050i signal, that is, 1050 scanning lines as an output image signal is performed.

[0063]

As described above, according to the present invention, when performing image information conversion, an arithmetic processing for performing prediction generation is performed together with prediction coefficient data for each class. Here, weight data is detected for each class based on a prediction coefficient calculated by a predetermined method.
By the rounding process using the weight amount data, the prediction coefficient for each class is converted into prediction coefficient data having a predetermined bit width.

For this reason, even when the value of the prediction coefficient greatly changes depending on the class, it is not necessary to increase the bit width allocated to the prediction coefficient in the coefficient memory, and the optimum calculation accuracy is ensured for each class. can do. Therefore, without increasing the capacity of the coefficient memory,
A wide range of prediction coefficient values can be supported.

For this reason, it is possible to effectively use the bit width allocated in the memory corresponding to the prediction coefficient without deteriorating the quality of the output image signal obtained by the image information conversion. Therefore, it is possible to reduce the total storage capacity of the memory for performing the storage corresponding to the prediction coefficient. For this reason, it is possible to contribute to reduction of the circuit scale and cost reduction relating to the entire device.

[Brief description of the drawings]

FIG. 1 is a schematic diagram illustrating an example of an arrangement of pixels in an image information conversion process performed according to an embodiment of the present invention.

FIG. 2 is a schematic diagram illustrating an example of a space class tap arrangement according to an embodiment of the present invention.

FIG. 3 is a block diagram illustrating an example of a configuration of a general image information conversion processing system.

FIG. 4 is a block diagram illustrating an example of a configuration of a general prediction coefficient calculation processing system.

FIG. 5 is a block diagram illustrating an example of a configuration of a prediction coefficient calculation processing system according to an embodiment of the present invention.

FIG. 6 is a block diagram illustrating an example of a configuration of an image information conversion processing system according to an embodiment of the present invention.

[Explanation of symbols]

29: maximum value detection circuit, 30: weight amount memory,
31: rounding processing unit, 32: coefficient memory

 ────────────────────────────────────────────────── ─── Continuing on the front page (72) Nobuyuki Asakura, Inventor 6-7-35 Kita-Shinagawa, Shinagawa-ku, Tokyo Inside Sony Corporation (72) Inventor Masashi Uchida 6-35, Kita-Shinagawa, Shinagawa-ku, Tokyo Inside Sony Corporation (72) Inventor Takuo Morimura 6-7-35 Kita-Shinagawa, Shinagawa-ku, Tokyo Sony Corporation (72) Inventor Kazutaka Ando 6-35, Kita-Shinagawa, Shinagawa-ku, Tokyo Soni -Inside the Corporation (72) Hideo Nakaya, Inventor 6-7-35 Kita-Shinagawa, Shinagawa-ku, Tokyo Sony Corporation Inside (72) Inventor Tsutomu Watanabe 6-35, 7-35 Kita-Shinagawa, Shinagawa-ku, Tokyo Soni Inside (72) Inventor Ken Ken Inoue 6-7-35 Kita-Shinagawa, Shinagawa-ku, Tokyo Sony Corporation (72) Inventor Wataru Niizuma 6-35, Kita-Shinagawa, Shinagawa-ku, Tokyo Sony Corporation Inside Term (Reference) 5C063 AA02 AA07 BA04 BA09 CA01 CA07

Claims (15)

[Claims] An image information conversion apparatus which forms an output image signal having a different scanning line structure from an input image signal, wherein a neighboring pixel having a predetermined positional relationship with respect to a predetermined point of interest is determined from the input image signal. First image data selecting means for selecting, and a pattern of a level distribution is detected from the image data selected by the first image data selecting means, and a space class to which the point of interest belongs is determined based on the detected pattern. A space class detecting means for determining a space class value to be indicated, and a second method for selecting, from the input image signal, neighboring pixels including the noted point and having a predetermined positional relationship with the noted point.
Image data selecting means, first storage means for storing prediction coefficient data predetermined for each space class, and weight data for the prediction coefficient data stored in the first storage means, A second storage unit for storing for each class, a prediction coefficient data selected from the first storage unit, and a weight amount data selected from the second storage unit according to the space class value. And an arithmetic processing means for performing arithmetic processing for estimating an output image signal based on the image data obtained by the second image data selecting means. 2. An image information conversion apparatus wherein an output image signal having a different scanning line structure is formed from an input image signal, wherein a neighboring pixel having a predetermined positional relationship with respect to a predetermined point of interest is determined from the input image signal. First image data selecting means for selecting, and a pattern of a level distribution is detected from the image data selected by the first image data selecting means, and a space class to which the point of interest belongs is determined based on the detected pattern. A space class detecting means for determining a space class value to be indicated; and a second image for selecting, from the input image signal, neighboring pixels having a predetermined positional relationship with the point of interest in a plurality of frames in the input image signal. Calculating a sum of absolute differences between frames from the image data selected by the data selecting means and the second image data selecting means; Motion class detection means for determining a motion class value representing motion based on the input image signal; class synthesis means for generating a class value by synthesizing the space class value and the motion class value; And selecting a neighboring pixel having a predetermined positional relationship with respect to the point of interest.
Image data selecting means, first storage means for storing prediction coefficient data predetermined for each space class, and weight data for the prediction coefficient data stored in the first storage means, Using second storage means for storing for each class, prediction coefficient data selected from the first storage means, and weight data selected from the second storage means according to the class value, An image information conversion device comprising: an arithmetic processing unit that performs an arithmetic process for estimating an output image signal based on image data obtained by the third image data selection unit. 3. The image processing device according to claim 2, wherein the weight amount data is selected by a true pixel value in a predetermined image signal having the same signal format as the output image signal, and by the third image data selection unit. An image information conversion apparatus, wherein a prediction coefficient is calculated so as to minimize a difference between the calculated linear data and a calculated value of a linear linear combination, and is determined for each class based on the calculated prediction coefficient. . 4. The method according to claim 2, wherein the input image signal is an interlace image signal having 525 scanning lines, and the output image signal is a progressive image signal having 525 scanning lines. Image information conversion device. 5. The method according to claim 2, wherein the input image signal is an interlaced image signal having 525 scanning lines, and the output image signal is a progressive image signal having 1050 scanning lines. Image information conversion device. 6. An image information conversion method in which an output image signal having a different scanning line structure is formed from an input image signal, wherein a neighboring pixel having a predetermined positional relationship with respect to a predetermined point of interest is determined from the input image signal. A first image data selection step of selecting, and a level distribution pattern is detected from the image data selected in the first image data selection step, and a space class to which the attention point belongs is determined based on the detected pattern. A space class detecting step of determining a space class value to be indicated, and a second step of selecting a neighboring pixel including the target point and having a predetermined positional relationship with the target point from the input image signal.
Image data selecting step, a first storing step of storing prediction coefficient data determined in advance for each space class, and a weight amount data for the prediction coefficient data stored in the first storing step, A second storage step of storing for each class, a prediction coefficient data selected from the first storage step, and a weight data selected from the second storage step according to the space class value. And an arithmetic processing step of performing an arithmetic processing for estimating an output image signal based on the image data obtained in the third image data selecting step. 7. An image information conversion method in which an output image signal having a different scanning line structure is formed from an input image signal, wherein a neighboring pixel having a predetermined positional relationship with respect to a predetermined point of interest is determined from the input image signal. A first image data selection step of selecting, and a level distribution pattern is detected from the image data selected in the first image data selection step, and a space class to which the attention point belongs is determined based on the detected pattern. A space class detecting step of determining a space class value to be indicated; and a second image selecting, from the input image signal, a neighboring pixel having a predetermined positional relationship with the target point in a plurality of frames in the input image signal. A data selection step, and a sum of inter-frame difference absolute values from the image data selected in the second image data selection step. Calculated, calculation results and the motion class detecting step of determining a motion class values representing movement based on, first by combining the above spatial class values and the motion class value
A class synthesis step of generating a class value of the following; and a third step of selecting, from the input image signal, a neighboring pixel including the target point and having a predetermined positional relationship with the target point.
Image data selecting step, a first storing step of storing prediction coefficient data determined in advance for each space class, and a weight amount data for the prediction coefficient data stored in the first storing step, A second storage step of storing for each class, a prediction coefficient data selected from the first storage step, and a weight data selected from the second storage step according to the space class value. And an arithmetic processing step of performing an arithmetic processing for estimating an output image signal based on the image data obtained in the second image data selecting step. 8. The method according to claim 7, wherein the weight amount data is selected by a true pixel value in a predetermined image signal having the same signal format as the output image signal, and the third image data selecting step. Image information conversion method, wherein a prediction coefficient is calculated so as to minimize a difference between the calculated linear data and a calculated value of a linear linear combination, and the class is determined for each class based on the calculated prediction coefficient. . 9. The method according to claim 7, wherein the input image signal is an interlaced image signal having 525 scanning lines, and the output image signal is a progressive image signal having 525 scanning lines. Image information conversion method. 10. The input image signal according to claim 7, wherein the input image signal is an interlaced image signal having 525 scanning lines, and the output image signal is a progressive image signal having 1050 scanning lines. Image information conversion method. 11. A television signal receiver in which an output image signal having a different scanning line structure is formed from an input image signal, wherein a neighboring pixel having a predetermined positional relationship with respect to a predetermined point of interest is defined as an input image signal. A first image data selecting means for selecting a pattern of a level distribution from the image data selected by the first image data selecting means, and a space class to which the point of interest belongs based on the detected pattern. A space class detecting means for determining a space class value indicating the following; and a second method for selecting, from the input image signal, neighboring pixels which include the noted point and have a predetermined positional relationship with the noted point.
Image data selecting means, first storage means for storing prediction coefficient data predetermined for each space class, and weight data for the prediction coefficient data stored in the first storage means, A second storage unit for storing for each class, a prediction coefficient data selected from the first storage unit, and a weight amount data selected from the second storage unit according to the space class value. And a calculation processing means for performing calculation processing for estimating an output image signal based on the image data obtained by the second image data selection means. 12. A television signal receiver in which an output image signal having a different scanning line structure is formed from an input image signal, wherein a neighboring pixel having a predetermined positional relationship with respect to a predetermined point of interest is defined as an input image signal. A first image data selecting means for selecting a pattern of a level distribution from the image data selected by the first image data selecting means, and a space class to which the point of interest belongs based on the detected pattern. A space class detecting means for determining a space class value indicating: a second pixel selecting a neighboring pixel having a predetermined positional relationship with the point of interest in a plurality of frames in the input image signal from the input image signal; Calculating a sum of absolute differences between frames from image data selected by the image data selecting means and the image data selected by the second image data selecting means; A motion class detecting unit that determines a motion class value representing a motion based on a result; a class synthesizing unit that generates a class value by synthesizing the space class value and the motion class value; A third step of selecting a neighboring pixel including the point of interest and having a predetermined positional relationship with the point of interest.
Image data selecting means, first storage means for storing prediction coefficient data predetermined for each space class, and weight data for the prediction coefficient data stored in the first storage means, Using second storage means for storing for each class, prediction coefficient data selected from the first storage means, and weight data selected from the second storage means according to the class value, A television signal receiver comprising: an arithmetic processing unit for performing an arithmetic process for estimating an output image signal based on image data obtained by the third image data selecting unit. 13. The weight image data according to claim 12, wherein the weight amount data is selected by a true pixel value in a predetermined image signal having the same signal format as the output image signal, and by the third image data selection means. A television signal receiving apparatus, wherein a prediction coefficient is calculated so as to minimize a difference between the calculated linear data and a calculated value of a linear linear combination, and the class is determined for each of the classes based on the calculated prediction coefficient. Machine. 14. The input image signal according to claim 12, wherein the input image signal is an interlace image signal having 525 scanning lines, and the output image signal is a progressive image signal having 525 scanning lines. Television signal receiver. 15. The method according to claim 12, wherein the input image signal is an interlace image signal having 525 scanning lines, and the output image signal is a progressive image signal having 1050 scanning lines. Television signal receiver.