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Prediction method of video compression

A prediction method and video compression technology, applied in the field of multimedia, can solve the problems such as the inability to further reduce the theoretical limit entropy operation complexity, the insufficient use of pixel texture correlation, the easy misjudgment of predicted pixel components, etc., and achieve excellent prediction effect and small size. The effect of predicting residual error and good correction effect

Active Publication Date: 2019-04-05
北京宏达一甲教育科技有限公司
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AI Technical Summary

Problems solved by technology

The existing texture correlation prediction methods have the following problems due to the small number of reference directions: 1) The components of the predicted pixels are easy to be misjudged, which affects the prediction results; 2) The prediction method does not make full use of the correlation between pixel textures and cannot further reduce Theoretical limit entropy and computational complexity

Method used

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  • Prediction method of video compression
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  • Prediction method of video compression

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Embodiment 1

[0060] See Figure 1 to Figure 11 , figure 1 Is a schematic flowchart of a prediction method in video compression provided by an embodiment of the present invention; figure 2 Is a schematic diagram of the algorithm principle of a prediction method in video compression provided by an embodiment of the present invention; image 3 Is a schematic diagram of a reference pixel position of a prediction method in video compression provided by an embodiment of the present invention; Figure 4 Is a schematic diagram of gradient value calculation of a prediction method in video compression provided by an embodiment of the present invention; Figure 5 This is a schematic diagram of reference value selection for a prediction method in video compression provided by an embodiment of the present invention. Image 6 Is a schematic diagram of MB division marking of a prediction method in video compression provided by an embodiment of the present invention; Figure 7 Is a schematic diagram of the o...

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Abstract

The invention relates to a prediction method of video compression. The method comprises that an image is divided into multiple MBs in the same size, and one MB is selected as an MB to be predicted; the MB to be predicted is predicted in a first prediction mode, and a first residual error subjective sum is obtained; the MB to be predicted is predicted in a second prediction mode, and a second firstresidual error subjective sum is obtained; and the first residual error subjective sum is compared with the second residual error subjective sum to select a final prediction mode of the MB to be predicted. A better prediction method can be selected from the first and second prediction modes via a prediction selection algorithm, and the prediction effect of a complex texture image is further optimized.

Description

Technical field [0001] The invention relates to the field of multimedia technology, in particular to a prediction method in video compression. Background technique [0002] With the development of network communication technology, the demand for watching videos on the computer and mobile terminals continues to increase. At the same time, people’s requirements for video quality are also increasing, which makes the video compression technology continuously improved. With the development, the International Organization for Standardization Other organizations have formulated a series of video communication standards, including H.261, H.262, H.263, H.264, MPEG-1, MPEG-2, MPEG-3, MPEG-4, AVS, etc. Nowadays, the latest video compression standard is the high-efficiency video coding standard HEVC, which is H.265 in the traditional sense. In real life, it is very necessary to use the bandwidth compression technology in the chip to improve the image storage space and transmission bandwidth...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N19/176H04N19/182H04N19/42H04N19/50
CPCH04N19/176H04N19/182H04N19/42H04N19/50
Inventor 田林海岳庆冬李雯
Owner 北京宏达一甲教育科技有限公司
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