Adaptive template prediction method used for bandwidth compression

An adaptive template and prediction method technology, applied in the field of compression, can solve problems such as poor correlation of image texture, reduction of theoretical limit entropy, and influence on the quality of prediction modules, etc., to achieve the goal of increasing bandwidth compression rate, reducing theoretical limit entropy, and improving accuracy Effect

Inactive Publication Date: 2019-03-08
XIAN CREATION KEJI CO LTD
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Problems solved by technology

[0004] However, when the texture of the image to be compressed is complex and changeable, when predicting the complex texture area of ​​the image to be compressed, the correlation between the image textures is often poor, and the predictive coding cannot get accurate references, resulting in the theoretical limit entropy. The reduction of maximization affects the quality of the prediction module

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  • Adaptive template prediction method used for bandwidth compression
  • Adaptive template prediction method used for bandwidth compression
  • Adaptive template prediction method used for bandwidth compression

Examples

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Embodiment 1

[0038] See figure 1 , figure 1 This is a flowchart of an adaptive template list prediction method provided by an embodiment of the present invention. The method includes the following steps:

[0039] Step 1. Create a list of adaptive templates;

[0040] Step 2. Initialize the adaptive template list;

[0041] Step 3. Select one or more candidate adaptive templates from the list of adaptive templates;

[0042] Step 4. Weighting the reconstruction value in the candidate adaptive template to obtain the prediction value of the current MB;

[0043] Step 5. Obtain the prediction residual of the current MB according to the predicted value.

[0044] In the adaptive template prediction method provided in this embodiment, by creating an adaptive template list, the adaptive template is adaptively extracted from the original image, and the reference pixel is selected for the current pixel based on the template, and then the prediction residual is calculated to solve the problem. When the texture of ...

Embodiment 2

[0046] In order to facilitate the understanding of the prediction method of the present invention, this embodiment describes the adaptive template list of the present invention in detail on the basis of the foregoing embodiment.

[0047] Specifically, see figure 2 , figure 2 It is a schematic diagram of an adaptive template list provided by an embodiment of the present invention. Establishing the adaptive template list includes: defining the number of adaptive templates and the serial number of the adaptive templates in the adaptive template list; wherein each of the adaptive templates corresponds to a set of reconstruction values ​​of one MB.

[0048] Preferably, the number of adaptive templates in the adaptive template list can be 4, 8, 16, or 32; taking 16 adaptive templates as an example, the sequence number of each adaptive template in the adaptive template list Arranged in order from 0 to 15. The smaller the adaptive template number, the higher the priority. Each adaptive t...

Embodiment 3

[0064] See image 3 , image 3 This is a flowchart of another method for predicting an adaptive template list provided by an embodiment of the present invention. This embodiment introduces in detail an adaptive template list prediction method proposed by the present invention on the basis of the foregoing embodiment. The prediction method includes the following steps:

[0065] Step 1. Update of adaptive template list

[0066] The default adaptive template list has been initialized and filled; then the adaptive template list is updated according to the adjacent direction MB of the current MB.

[0067] Specifically, updating the adaptive template list according to the neighboring direction MB of the current MB includes: detecting the reconstruction value of the MB in the neighboring direction of the current MB; judging the reconstruction value of the MB in the neighboring direction and the self Whether the filling reconstruction values ​​in the adaptive template list are consistent to...

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Abstract

The invention relates to an adaptive template prediction method used for bandwidth compression. The method comprises the following steps: step 1, building an adaptive template list; step 2, performinginitial filling for the adaptive template list; step 3, selecting a reference MB, and updating the adaptive template list according to the reference MB; step 4, selecting one or more candidate adaptive templates from the updated adaptive template list; step 5, weighting the candidate adaptive templates to obtain a predicted value of the current MB; step 6, acquiring a predicted residual error ofthe current MB according to the predicted value. In the adaptive template prediction method provided by the invention, through customizing the adaptive template, selecting reference pixels for the current pixel according to the template and then calculating the predicted residual error, a problem of how to improve quality of a prediction module when texture of a to-be-compressed picture is complicated and changeable is solved, and theoretic limit entropy can be reduced further.

Description

Technical field [0001] The present invention relates to the technical field of compression, in particular to an adaptive template prediction method for bandwidth compression. Background technique [0002] The video signal contains a huge amount of information, which is difficult to store and transmit; therefore, it is necessary to compress the video signal. After the video is compressed, it will be more convenient to store. For example, in a 60-second video work, each frame of the image has the same chair at the same position, it is not necessary to save the data of this chair in each frame of the image. For another example, there are billions of colors, but we can only distinguish about 1024 types, because we can't perceive the subtle difference between a color and its neighboring colors, so there is no need to keep every color. Because the video image data has a strong correlation, that is to say there is a lot of redundant information, the redundant information in the video s...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N19/50H04N19/85H04N19/182
CPCH04N19/50H04N19/182H04N19/85
Inventor 罗瑜张莹冉文方
Owner XIAN CREATION KEJI CO LTD
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