JPH0795411A - Picture data compressing method - Google Patents

Abstract

PURPOSE:To use the visual characteristic of human eyes to obtain a satisfactorily compressed picture with a smaller number of bits by limiting the change range of variable density to a minute block unit like a prescribed number of picture elements to quantize each picture element. CONSTITUTION:Digital data Y quantized by an A/D converter 21 is divided into blocks B by a block dividing circuit 22, and a maximum value MAX and a minimum value MIN of data Y in each block are taken out by a detecting circuit 23. Data Y from the circuit 22 is delayed and compensated by a delay circuit 24, and data Y of the block B is divided into subblocks SB by a block dividing circuit 25, and a maximum value SMAX and a minimum value SMIN in each eubblock SB are taken out by a detecting circuit 26. A D-range encoding circuit 28 encodes SMAX and SMIN in the range determined by MAX and MIN. A D-range decoding circuit 29 obtains the output of the circuit 28 to output SMAX' and SMIN', and a quantizing circuit 30 quantizes data Y of the subblock SB in the range determined by SMAX' and SMIN'.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method of compressing image data.

[0002]

2. Description of the Related Art In computer graphics, a color display capability of 256 colors per pixel is generally sufficient. In other words, it is sufficient to allocate 8 bits to 1 pixel.

However, recently, there is a demand for processing and displaying a natural image, for example, an image captured by a video camera, and in this case, the color display capability of 256 colors per pixel is insufficient.

However, since the computer graphics has a display capacity of about 2000 pixels × 2000 pixels, if the color display capacity per pixel is increased, the size of the display memory becomes too large. For example, if 8 bits are assigned to each of R, G, and B components in one pixel, 24 bits are required for each pixel, so that 24 bits x 2000 pixels x 2000 pixels = 96000 as a whole.
The size becomes 000 bits ≈ 11.4 megabytes, which takes a lot of time when transmitting the image data, or even if a hard disk device is used, only a small number of images can be stored. In any case, it becomes less practical.

Therefore, there is a compression method called the ADRC method as a method for compressing image data without degrading the image quality, particularly the resolution.

FIG. 3 shows an example of an image data compression circuit for compressing image data by the ADRC method, which is a grayscale image signal Y.
However, 1 sample (1 pixel) in A / D converter 1
Is quantized into 8-bit digital data Y, and this data Y is 16 pixels (=
It is divided into one block B for each 4 lines × 4 pixels), and the maximum value MAX and the minimum value MIN of the data Y in that block are taken out for each block in the detection circuit 3.

Then, in the subtraction circuit 4, 8-bit data D indicating the dynamic range D is extracted from these data MAX and MIN. In addition, the division circuit 2
The data Y from is subjected to delay compensation with respect to the detection circuit 3 in the delay circuit 5, and then in the subtraction circuit 6, the delay compensated data Y and the data MIN are cut off from the minimum value MIN or less ( Y-MIN) is extracted and supplied to the adaptive encoder 7, and the data D is supplied to the encoder 7 so that, for each block B, each data Y is an 8-bit data Y indicating an absolute level. In the section D, the 4-bit grayscale data DATA with the level MIN as a reference is requantized.

Therefore, the data Y of one block B
In contrast, 4 bits x 16 samples of gradation data DAT
A, 8-bit minimum value data MIN, and 8-bit dynamic range data D are obtained, and these data are transmitted or accumulated.

FIG. 4 shows an example of an image data decompression circuit for obtaining the original grayscale image signal Y from the data DATA, which has been subjected to the processing reverse to that of the adaptive encoder 7 and the subtraction circuit 6. The data Y is reconstructed into 8-bit data Y, and the data Y is arranged in the block decomposition circuit 13 by one sample in order of the original time axis. When this is supplied to the D / A converter 14, the original grayscale image signal Y is extracted. Be done.

Reference: Journal of the Institute of Electronics, Information and Communication Engineers, April 1987
Month issue pages 720-726, 736-741

[0011]

In order to improve the compression rate by the ADRC method, it is possible to increase the block size and reduce the number of quantization bits of the grayscale data DATA. However, as in the conventional example, the gradation data DA
When the number of quantization bits of TA is 4, the compression rate cannot be more than double, no matter how large the block size is. Therefore, in order to double the compression rate, it is indispensable to reduce the number of allocated bits of the gradation data DATA. The reduction of the number of quantization bits causes a quantization error. When encoding a block including contours, its dynamic range naturally becomes large, and the quantization resolution becomes coarse with a small bit allocation. Therefore, there is a problem that the block including the contour has a large quantization error of the entire block, and the quantization noise is noticeable and the image becomes unnatural compared to the block not including the contour.

The object of the present invention is to concentrate the quantization error only in the very vicinity of the contour, and by utilizing the visual characteristics of the human eye, image data in which a good compressed image can be obtained with a smaller number of bits. The purpose is to obtain a compression method.

[0013]

An image data compression method according to the present invention comprises means for dividing an image into minute blocks B, means for obtaining the maximum value MAX and the minimum value MIN of the minute blocks B, and the minute blocks B. Means for dividing into smaller micro blocks SB and maximum value S of the micro blocks SB
Means for obtaining MAX and minimum value SMIN, and maximum value SMA
Means for quantizing X and the minimum value SMIN within a range determined by the maximum value MAX and the minimum value MIN, and a quantized maximum value S
Maximum value SMA by dequantizing MAX and minimum value SMIN
Means for obtaining X ′ and the minimum value SMIN ′, and the small block S
It is characterized in that it comprises means for quantizing the light and shade of B within the range defined by the maximum value SMAX 'and the minimum value SMIN'.

[0014]

DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail below with reference to the drawings showing the embodiments thereof. FIG. 1 is a block diagram showing a configuration example of an image data compression circuit for carrying out the present invention.

The grayscale image signal Y is transferred to the A / D converter 21.
At, one pixel is quantized into 8-bit digital data Y. This data Y is divided by the block division circuit 22 into one block B for every 64 pixels (8 lines × 8 pixels), and further, in the first detection circuit 23, the data in the block B is divided for each block B. 8-bit data MAX and MIN indicating the maximum value MAX and the minimum value MIN of Y are taken out. Further, the data Y from the block division circuit 22 is subjected to delay compensation for the detection circuit 23 in the first delay circuit 24, and then the second
Block division circuit 25 divides the data Y of block B into 16 sub-blocks SB [i] (2 lines × 2 pixels) as shown in FIG. 5, and the second detection circuit 26 sub-block SB [i]. Maximum value SMAX of data Y for each i]
SMAX indicating [i] and minimum value SMIN [i]
[I] and SMIN [i] are taken out. In addition, the data Y from the block division circuit 25 is transferred to the second delay circuit 27.
In, the delay compensation for the detection circuit 26 is performed.

The D-range coding circuit 28 divides the range defined by MAX and MIN into, for example, four, as shown in FIG.
The area to which AX [i] and SMIN [i] belong is checked and encoded. As shown in FIG. 6, if the threshold value for dividing into four equal parts is th0, th1, and th2 from the bottom, SMAX [i]
Is between MIN and th0, “0” is set as the code CODE0 [i] indicating the maximum value, and SMAX [i] is t.
When it is between h0 and th1, the code CODE0 [i]
Is “1”, and when SMAX [i] is between th1 and th2, “2” is given as the code CODE0 [i].
When SMAX [i] is between th2 and MAX, "3" is output as the code CODE0 [i]. Similarly, when SMIN [i] is between MIN and th0, “0” is set as the code CODE1 [i] indicating the minimum value.
When SMIN [i] is between th0 and th1, “1” is set as the code CODE1 [i],
When [i] is between th1 and th2, the code COD
“2” is output as E1 [i], and “3” is output as code CODE1 [i] when SMIN [i] is between th2 and MAX.

The D range decoding circuit 29 uses these codes C
Enter ODE0 [i] and CODE1 [i] to enter CODE
When it is 0, the upper threshold value is output, and when it is CODE 1, the lower threshold value is output. That is, when the code CODE0 [i] is "0", "1", "2", "3", SMAX '
Th0, th1, th2, and MAX as [i], respectively
Is output, and the code CODE1 [i] is “0”, “1”,
When it is "2" or "3", MIN, th0, th1 and th2 are output as SMIN '[i].

SMAX 'and S obtained as described above
MIN 'represents the range of change of the data Y in the block SB [i]. The quantization circuit 30 uses SMAX 'and SM.
Within the range determined by IN ′, each data Y of the block SB [i] input from the delay circuit 27 is quantized with, for example, 2 bits, and data DATA [i] is quantized as a representative value.
[J] (j represents pixel data in the block SB, j =
0 to 3. ) Is output. As described above, the pixel data of the block B is set to the blocks SB [0] to SB [1.
5] are sequentially encoded.

Therefore, for the data Y of block B,
2 × 4 × 16 gradation data DATA and 2 × 16 code data CODE0 [16] and CODE1 [16]
Then, 8-bit maximum value data MAX and 8-bit minimum value data MIN are obtained, and these data are transmitted or accumulated.

Next, an embodiment of the image data expansion circuit according to the present invention will be described in detail. FIG. 2 is a block diagram showing a configuration example of an image data expansion circuit for implementing the present invention.
First, MAX, MIN, CODE0 [i], CODE1
[I] is input and supplied to the D range decoding circuit 31.
Like the D range decoding circuit 29, the D range decoding circuit 31 outputs the upper limit threshold value when CODE0 [i] is input, and inputs the lower limit threshold value when CODE1 [i] is input. . For example, the thresholds that divide the range represented by MAX and MIN into four equal parts are th0, th1, and th from the bottom.
If the value is 2, when "2" is input as CODE0 [i], the range corresponding to "2" is between th1 and th2, and CODE0 [i] is a code representing the maximum value, so that the output SMAX '[i] becomes th2. CODE
When "0" is input as 0 [i], the output SMI
N ′ [i] becomes MIN.

The SMAX '[i] and SMIN' [i] obtained as described above are each data Y of the block SB [i].
, Which is supplied to the inverse quantization circuit 32. The inverse quantization circuit 32 simultaneously receives data DATA [i]
Enter [j]. The inverse quantization circuit 32 uses SMAX '.
The quantized value corresponding to the data DATA [i] [j] is selected from the quantized values within the range defined by [i] and SMIN ′ [i], and is set as the data Y of each pixel. The data Y is arranged in the block decomposition circuit 33 in the order of the original time axis by one sample, and the original grayscale image signal Y is taken out when the data Y is supplied to the D / A converter 34.

[0022]

As described above, according to the present invention, the variation range of the light and shade is limited to a small block unit of about 2 lines × 2 pixels and each pixel is quantized, so that only the outline portion is roughly quantized. Since the flat part near the contour is finely quantized, it is possible to perform quantization that matches the visual characteristics of the human eye, and the image can be compressed at a compression ratio of 2 times or more without degrading the image quality. It has the effect of compression.

[Brief description of drawings]

FIG. 1 is a block diagram showing the configuration of an embodiment of an image data compression circuit of the present invention.

FIG. 2 is a block diagram showing a configuration of an embodiment of an image data expansion circuit of the present invention.

FIG. 3 is a block diagram showing a configuration of a conventional image data compression circuit.

FIG. 4 is a block diagram showing a configuration of a conventional image data expansion circuit.

FIG. 5 is a block division circuit 2 according to an embodiment of the present invention.
The figure which shows the block division | segmentation method of 5.

FIG. 6 is a diagram for explaining the operation of the D range encoding circuit 28 according to the embodiment of the present invention.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 A / D converter 2 Block division circuit 3 Detection circuit 4 Subtraction circuit 5 Delay circuit 6 Subtraction circuit 7 Adaptive encoder 11 Adaptive decoder 12 Addition circuit 13 D / A converter 21 A / D converter 22 Block division circuit 23 Detection circuit 24 Delay circuit 25 block division circuit 26 detection circuit 27 delay circuit 28 D range encoding circuit 29 D range decoding circuit 30 quantization circuit 31 D range decoding circuit 32 inverse quantization circuit 33 block decomposition circuit 34 D / A converter

Claims (1)

[Claims] 1. A means for dividing an image into minute blocks B,
A means for obtaining the maximum value MAX and the minimum value MIN of the minute block B, and the minute block B having a smaller minute block S.
Means for dividing into B and maximum value SMA of minute block SB
Means for obtaining X and the minimum value SMIN, means for quantizing the maximum value SMAX and the minimum value SMIN within a range determined by the maximum value MAX and the minimum value MIN, and a quantized maximum value SMA.
A means for dequantizing X and the minimum value SMIN to obtain a maximum value SMAX 'and a minimum value SMIN', and a means for quantizing the light and shade of the minute block SB within a range determined by the maximum value SMAX 'and the minimum value SMIN'. A method for compressing image data, comprising: