JP2950559B2 - Image processing method and apparatus - Google Patents

Description

Description: BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing method and apparatus for compressing and transmitting or recording a still image with data.

[Conventional technology]

“Baseline S” to standardize the natural image coding system
Various international standardization schemes such as "ystem" and "Extended System" have been proposed.

FIG. 3 is a schematic diagram showing the processing procedure of the "Baseline System" of the international standardized system. This system divides an input image into blocks of 8 × 8 pixels, and performs discrete cosine transform (DCT) for each block.
m) (process P1), and the obtained DCT coefficient is divided by each threshold of a quantization matrix composed of 8 × 8 thresholds to perform quantization (process P2). FIG. 4 is a diagram showing an example of a quantization matrix for a luminance signal.

A difference between the DC component of the quantized DCT coefficient and the DC component quantized in the previous block is obtained, and the number of bits of the difference is Huffman-coded (processing P3 and P4). After the AC component is zigzag scanned in the block and converted into a one-dimensional sequence, two-dimensional Huffman coding is performed on the number of consecutive zeros (ineffective coefficients) and the number of bits of effective coefficients (processing P3 and P3). P4). FIG. 5 is a table showing an example of the zigzag scan order.

At the time of quantization in the process P2, a certain coefficient (scale factor) is set for each threshold value of the quantization matrix.
Are multiplied and then quantized. The image quality and the compression ratio of the compressed image are adjusted by the scale factor.

The data thus compressed is decompressed by a process reverse to the processes P1 to P4. That is, Huffman decoding in process P4 ', decoding of DC and AC components in process P3', inverse quantization in process P2 ', and inverse DCT (IDCT) in process P1'.

[Problems to be solved by the invention]

By the way, in the above-described processing procedure, if the scale factor is fixed at a fixed value and quantized, there is a disadvantage that the quality of the image changes depending on the content of the compressed image.

In general, a single image contains a small portion of a pattern in which the image signal changes rapidly and a flat portion in which the image signal changes relatively slowly. The compression ratio cannot be raised too high to maintain quality. Conversely, in an image having a large area of a flat portion, the deterioration of the image quality is small even if the compression ratio is increased.

Therefore, an object of the present invention is to provide an image processing method and apparatus capable of changing the value of a scale factor depending on the content of an image to be compressed and keeping the quality of a compressed image almost constant.

[Means for solving the problem]

According to the present invention, an input image is divided into a plurality of blocks each composed of n × n pixels, and a discrete cosine transform is performed for each block. In an image processing method including a compression step of performing quantization using a quantization matrix including × n threshold values, a block belonging to a flat portion of an image whose signal conversion is gentler than a discrete cosine transform coefficient in each block. Whether or not the threshold value is obtained is multiplied by a coefficient b obtained as a function of the ratio of the number of the divided blocks to each threshold value of the n × n quantization matrices, and then quantization is performed.

Also, the input image is divided into a plurality of blocks each composed of n × n pixels, and means for performing discrete cosine transform for each block, and n × n transform coefficients obtained by the conversion are represented by n In an image processing apparatus provided with data compression including means for performing quantization using a quantization matrix composed of × n threshold values, a flat portion of an image in which a signal change is gentler than a discrete cosine transform coefficient in each block. Means for classifying whether or not the block belongs to, and means for multiplying a coefficient b obtained as a function of the ratio of the number of the divided blocks by each threshold value of the n × n quantization matrices, The quantization is performed using the multiplied quantization matrix.

[Operation] In the image processing according to the present invention, when compressing image data by a process such as discrete cosine transform, the content of the image to be compressed is fine in a pattern in which the image signal changes drastically, or the image signal changes slowly. The scale factor at the time of quantization is changed in accordance with the degree of flatness so that the quality of the compressed image is kept almost constant.

The determination of whether the content of the image is fine or flat is performed by detecting the DCT spectrum of each block constituting one image. By this detection, the area ratio between the fine part and the flat part of the picture in one image, in other words, the area ratio of the fine part or the flat part of the picture with respect to the whole area of one image is obtained, and a visual test is performed in advance. Then, a scale factor corresponding to the area ratio obtained from the relationship between the area ratio and the scale factor obtained in is obtained. After multiplying the thus obtained scale factor by each threshold value of the quantization matrix, quantization is performed.

In this way, the scale factor can be changed according to the content of the image to be compressed, and the quality of the compressed image can be kept almost constant.

〔Example〕

FIG. 1 is a schematic diagram showing a processing procedure of image processing according to the present invention, and the same parts as those in FIG.

First, an input image is divided into blocks each including n dots in a horizontal direction and n × n pixels of a line in a vertical direction, for example, 8 × 8 pixels, and a discrete cosine transform (DCT) is performed for each block.
(Process P1).

The DCT coefficient obtained by this DCT is divided by each threshold value of a quantization matrix composed of 8 × 8 threshold values and quantization is performed (processing P2). The DC component of the quantized DCT coefficient is quantized by the previous block. The difference from the converted DC component is obtained, and the number of bits of the difference is Huffman-coded. The AC component is subjected to zigzag scanning within the block and converted into a one-dimensional sequence, and then two-dimensional Huffman coding is performed on the number of consecutive zeros (ineffective coefficients) and the number of effective coefficient bits (processing P3 and P3). P4).

Huffman coding does not use the quantized coefficient value itself for both the DC and AC components, and the number of bits required to represent the value is the target of Huffman coding. Then, apart from the Huffman code, the value of the number of bits is added as additional information. For example, if the quantized coefficient is 2 (decimal number), it is represented as “000... 010” in a binary number, and the number of bits 2 required to represent this is a value representative of this value. Huffman coding is performed, and 2-bit data “10” is added as additional bits.

On the other hand, when the quantized coefficient is negative, data obtained by subtracting 1 from the additional bit is added. For example, if the quantized coefficient is -2 (decimal number), it is expressed as a binary number (two's complement notation), "111 ... 110", and the lower two bits are additional bits. “01” obtained by subtracting “1” is added as an additional bit. By doing so, the additional bit starts with 1 when the quantized coefficient is positive, and starts with 0 when the quantized coefficient is negative.

In addition, at the time of quantization in the process P2, each threshold value of the quantization matrix is multiplied by a scale factor corresponding to the content of the image to be compressed, and obtained in process 1 in order to keep the quality of the compressed image almost constant. The scale factor is determined based on the obtained DCT coefficient (process P5).

The image content is determined based on the DCT coefficient obtained in the processing 1. That is, assuming that the DCT coefficient is Cij (i, j = 1, 2,..., 8), the absolute value | Cij | represents the magnitude of each frequency component of the image of the block. Therefore, if the image content is flat and the signal changes slowly, the absolute value | Cij | when i and j are large will be small. Conversely, if the image is fine and the signal changes drastically, the absolute value | Cij | increases and high frequency components increase.

Therefore, the area ratio between the fine part and the flat part of the picture in one image, in other words, the area ratio of the fine part or the flat part of the picture with respect to the entire area of one image, is determined in advance by a visual test. A scale factor corresponding to the image content is obtained from the relationship between the obtained area ratio and the scale factor.

Next, a method of determining the scale factor will be described with reference to the flowchart of FIG. In the following description, it is assumed that the area ratio of a small portion of a picture to the entire area of one image is obtained, and the scale factor is obtained from the area ratio.

First, a counter m is reset in order to count the number of blocks in a fine portion of a picture in one image (step
S1).

Next, the DCT coefficients of the first block (n × n pixels) are input (step S2), and the absolute value of each coefficient is calculated (step S3). This absolute value is calculated by calculating the DCT coefficient of one block as C
ij (i, j = 1,2, ..., 8), a value a defined by the following equation
Is calculated.

This value a represents the ratio of the reduced component to the entire DCT absolute value spectrum. The high frequency component of the DCT spectrum increases when the block belongs to a fine portion of the picture, and decreases when the block belongs to a flat portion. Therefore, it can be determined from the DCT spectrum whether the block belongs to a fine part or a flat part of the picture, and a larger value a indicates that the picture is flatter. Then, when the threshold value V is determined and a <V is satisfied, it can be determined that the block belongs to the fine portion of the picture (step S4).

Next, the number of blocks belonging to the fine part of the picture is counted (step S5), and it is determined whether or not these processes have been performed for all the blocks of one image (step S6). The number of blocks belonging to a small portion of the picture for all blocks in the image is obtained.

The number of blocks m of the fine part of the pattern obtained in this way is
By dividing by the total number of blocks M, a parameter r indicating the image content is obtained (step S7), a scale factor b is obtained from the parameter r by a function f obtained by a visual test (step S8), and the process is terminated.

In the above-described embodiment, the reason that the absolute value is used to obtain the value indicating the image content is that the hardware configuration is easy, and as another method, the power is calculated by squaring. It may be determined or an effective value may be adopted.

〔The invention's effect〕

According to the present invention, since the scale factor can be changed depending on the content of the image to be compressed, the quality of the compressed image can be kept almost constant.

[Brief description of the drawings]

1 is a diagram showing a processing procedure of image processing according to the present invention, FIG. 2 is a flowchart showing processing for determining a scale factor in FIG. 1, FIG. 3 is a diagram showing a processing procedure of conventional image processing, FIG. 4 is a diagram showing a quantization matrix of a luminance signal, and FIG. 5 is a diagram showing a table of zigzag scan.

Continuation of the front page (58) Field surveyed (Int.Cl. ⁶ , DB name) H04N 1/41-1/419 H04N 7/24-7/68

Claims (4)

(57) [Claims] 1. An input image is divided into a plurality of blocks each composed of n × n pixels, and a discrete cosine transform is performed for each block. In an image processing method including a compression step of performing quantization using a quantization matrix composed of n × n threshold values, a block belonging to a flat portion of an image whose signal change is more gradual than a discrete cosine transform coefficient in each block. Whether or not there is, and multiplying each threshold of the n × n quantization matrices by a coefficient b obtained as a function of the ratio of the number of the divided blocks, and then performing the quantization. Image processing method. 2. Classification of whether or not a block belongs to a flat part of the image is performed by using a discrete cosine transform coefficient in the block.
Cij (i, j = 1,2 ..., n) Calculate the parameter a defined by
2. The image processing method according to claim 1, wherein the image data is classified based on whether or not is greater than or equal to a predetermined threshold value. 3. An input image is divided into a plurality of blocks each consisting of n.times.n pixels, and a discrete cosine transform is performed for each block; and n.times.n transform coefficients obtained by the conversion. In an image processing apparatus provided with data compression including means for performing quantization using a quantization matrix composed of n × n threshold values, the image processing apparatus performs image processing in which the signal change is gentler than the discrete cosine transform coefficient in each block. Means for classifying whether or not the block belongs to a flat portion, and means for multiplying each threshold of the n × n quantization matrix by a coefficient b obtained as a function of the ratio of the number of the divided blocks. And an image processing apparatus for performing the quantization using the multiplied quantization matrix. 4. The dividing means sets discrete cosine transform coefficients in a block to Cij (i, j = 1, 2,..., N), Calculate the parameter a defined by
4. The image processing apparatus according to claim 3, wherein the image data is classified based on whether or not is greater than or equal to a predetermined threshold value.