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Video coding and decoding method and device based on image super-resolution

A super-resolution and video coding technology, applied in image communication, digital video signal modification, electrical components, etc., can solve the problem of difficult to restore high-frequency detail information of high-resolution images, restricting the efficiency of sub-pixel motion compensation, blurring of edges, etc. problems, to achieve the effect of avoiding blurred edges, improving accuracy, and improving coding efficiency

Active Publication Date: 2014-12-24
PEKING UNIV SHENZHEN GRADUATE SCHOOL
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The advantage of the linear interpolation method is that it is simple, but the disadvantage is that it is difficult to restore the high-frequency detail information of the high-resolution image, and at the same time blur the edge, thus restricting the efficiency of sub-pixel motion compensation

Method used

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  • Video coding and decoding method and device based on image super-resolution
  • Video coding and decoding method and device based on image super-resolution
  • Video coding and decoding method and device based on image super-resolution

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Experimental program
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Embodiment 1

[0025] Please refer to figure 1 , figure 1 It is a flowchart of an image super-resolution-based video encoding method in an embodiment. Such as figure 1 As shown, this embodiment provides a video coding method based on image super-resolution, which may include the following steps:

[0026] 101. Perform super-resolution interpolation processing on the video image to be coded by using a pre-trained texture dictionary library.

[0027] After super-resolution interpolation processing, the reference image is obtained. The texture dictionary library includes: one or more sets of dictionary bases, the dictionary bases are: a mapping group consisting of high-resolution image blocks of training images and low-resolution image blocks corresponding to the high-resolution image blocks, The super-resolution interpolation processing includes: image enlargement and image detail information restoration.

[0028] 102. Perform motion estimation and motion compensation on the reference imag...

Embodiment approach

[0036] S1. Select a plurality of high-resolution local image blocks from a training image set including several training images, wherein a high-resolution local image block is composed of at least two pixels on the image where it is located. The training image is down-sampled to obtain low-resolution local image blocks corresponding to each local image block.

[0037]S2. Extracting local features of high-resolution local image blocks to obtain high-resolution dictionary samples Dh(y), and extracting local features of low-resolution local image blocks corresponding to each of the local image blocks to obtain Low-resolution dictionary samples Dl(y), mapping and combining the high-resolution dictionary samples and the low-resolution dictionary samples to obtain a set of dictionary base samples, the local features include LBS and SES.

[0038] S3. Perform training on the multiple sets of dictionary base samples to obtain a texture dictionary library.

[0039] The process and prin...

Embodiment 2

[0064] Please refer to image 3 , image 3 It is a flowchart of an implementation manner of step 101 in the first embodiment. In this embodiment, each dictionary base in the texture dictionary is classified according to the local features of the high-resolution image blocks of each training image and the local features of the low-resolution image blocks corresponding to the high-resolution image blocks, the Local features include local binary structure and sharp edge structure.

[0065] The video encoding method based on image super-resolution provided in this embodiment uses the pre-trained texture dictionary library to perform super-resolution interpolation processing on the video image to be encoded, which may specifically include the following steps:

[0066] 101a. Extract local features of each image block on the video image to be encoded.

[0067] 101b. Match the local features of each image block in the video image to be encoded with the local features of each dictio...

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Abstract

The invention provides a video coding and decoding method and device based on the image super-resolution. According to the method, before a video image to be coded or decoded is predicted, the super-resolution interpolation processing is carried out on the video image to be coded or decoded, amplifying and detailed information recovering can be carried out on the video image to be coded or decoded, and therefore when the video image to be coded or decoded is predicted to obtain a prediction block, compared with a method for predicting the video image through the linear interpolation in the prior art, the original image can be restored more effectively, the problem that the edge of a prediction block is blurry in the prior art is avoided, and the prediction accuracy of the video image is enhanced, and accordingly the coding efficiency of the video image is improved.

Description

technical field [0001] The present invention relates to the technical field of image super-resolution, in particular to a video encoding and decoding method and device based on image super-resolution. [0002] Background technique [0003] The traditional coding method is to use the information redundancy of the image to be encoded and the video itself to compress the video image. With the continuous improvement of encoding technology, the redundancy of video encoding is continuously reduced. Correlation is fully exploited. Predicting the image and video information to be encoded with the help of information other than the image and video to be encoded, thereby reducing the amount of information of the image and video to be encoded, is a new direction to greatly improve the efficiency of image and video compression. [0004] In the prior art, in order to improve the efficiency of inter-frame prediction of video images, sub-pixel motion compensation technology is generally ...

Claims

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Application Information

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IPC IPC(8): H04N19/53
Inventor 王荣刚赵洋王振宇高文王文敏董胜富黄铁军马思伟
Owner PEKING UNIV SHENZHEN GRADUATE SCHOOL