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Video compression prediction method

A prediction method and video compression technology, applied in digital video signal modification, image communication, electrical components, etc., can solve problems such as poor correlation, reduction of theoretical limit entropy, and impact on the quality of prediction modules, so as to improve accuracy, good deviation correction effect, Optimizing the performance of predictive performance

Inactive Publication Date: 2020-05-05
XIAN CREATION KEJI CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, when the texture of the image to be compressed is complex and changeable, the correlation is often poor when predicting the complex texture area of ​​the image to be compressed, and the predictive coding cannot get an accurate reference, resulting in the reduction of the theoretical limit entropy. Predicting the quality of the module has become a problem that needs to be solved at present

Method used

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Embodiment 1

[0055] See figure 1 , figure 1 It is a flowchart of a video compression prediction method provided by the present invention. The prediction method of the present embodiment includes the following steps:

[0056] S1: Divide the image into multiple MBs of the same size, and select one MB as the current MB;

[0057] S2: Predict the current MB by using a prediction method based on pixel-level multi-component reference, and obtain a first prediction residual of the current MB;

[0058] S3: Predict the current MB by using an adaptive texture gradient prediction method based on inflection point sampling, and obtain a second prediction residual of the current MB;

[0059] S4: Select a final prediction residual of the current MB according to the first prediction residual and the second prediction residual.

[0060]Further, step S2 includes:

[0061] S21: Select the current pixel, and determine multiple pixel components of the current pixel;

[0062] S22: Calculate pixel differenc...

Embodiment 2

[0098] See Figure 4 with Figure 5 , Figure 4 A schematic diagram of gradient value calculation provided by the embodiment of the present invention; Figure 5 It is a flow chart of another adaptive direction prediction method for pixel-level multi-component reference provided by an embodiment of the present invention. On the basis of the above-mentioned embodiments, this embodiment describes the pixel-level multi-component reference adaptive direction prediction method proposed by the present invention by way of example. In this embodiment, the current pixel is divided into R component, G component and B component, specifically as follows:

[0099] For the three components of the current pixel, determine the three texture direction gradient values ​​G1, G2, and G3 of each component through the surrounding components of each component;

[0100] Preferably, for the R component, the G component, and the B component, according to Figure 4 As shown, ABS(K-H) is a gradient v...

Embodiment 3

[0121] See Image 6 , Image 6 It is a flow chart of a prediction method for adaptive texture gradient based on knee point sampling provided by an embodiment of the present invention. The forecasting method includes the steps of:

[0122] S31: Determine the sampling mode of the current MB;

[0123] S32: Determine the sampling point of the current MB by using a pixel value inflection point sampling method;

[0124] S33: Select multiple prediction modes to predict the sampling points of the current MB, and acquire multiple prediction residuals corresponding to each prediction mode;

[0125] S34: Calculate the residual absolute value sum of each prediction mode, and determine the final prediction mode of the current MB;

[0126] S35: Calculate a second prediction residual of the current MB according to the final prediction manner.

[0127] In this embodiment, step S32 includes:

[0128] S321: Calculate the difference between the pixel value of the current pixel component of...

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Abstract

The invention relates to a video compression prediction method, which comprises the following steps of: dividing an image into a plurality of MBs with the same size, and selecting one MB as a currentMB; predicting the current MB through a prediction method based on pixel-level multi-component reference to obtain a first prediction residual error of the current MB; predicting the current MB through an adaptive texture gradient prediction method based on inflection point sampling to obtain a second prediction residual error of the current MB; and selecting a final prediction residual error of the current MB according to the first prediction residual error and the second prediction residual error. According to the method, the optimal prediction method is selected from a prediction method based on pixel-level multi-component reference and a prediction method based on inflection point sampling and adaptive texture gradient through a prediction selection algorithm, and the prediction effectof a complex texture image can be further optimized.

Description

technical field [0001] The invention belongs to the technical field of video compression, and in particular relates to a video compression prediction method. Background technique [0002] With the gradual increase of people's demand for video quality, video image resolution is one of the important characteristics of video quality. For video processing chips, the multiple increase in resolution will not only cause a substantial increase in chip area cost, but also have a great impact on bus bandwidth and power consumption. In order to overcome this problem, the bandwidth compression technology applied in the chip is proposed. Different from port compression, the goal of on-chip bandwidth compression is to increase the compression factor as much as possible and reduce the occupation of DDR (Double Rate Synchronous Dynamic Random Access Memory) with a smaller logic area cost. [0003] Bandwidth compression is mainly composed of four parts, including: prediction module, quanti...

Claims

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Application Information

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IPC IPC(8): H04N19/103H04N19/176H04N19/186
CPCH04N19/103H04N19/176H04N19/186
Inventor 田林海李雯岳庆冬
Owner XIAN CREATION KEJI CO LTD
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