Video super-resolution method based on compressed domain

A super-resolution and compressed domain technology, applied in digital video signal modification, television, electrical components, etc., can solve the problem that low-resolution image pixels cannot be observed or predicted by target frame motion compensation

Active Publication Date: 2010-03-17
ZHEJIANG UNIV
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  • Abstract
  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

But in fact, the low-resolution image pixels in some windows cannot be observed or predicted by the motion compensation of the target frame

Method used

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  • Video super-resolution method based on compressed domain
  • Video super-resolution method based on compressed domain
  • Video super-resolution method based on compressed domain

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Embodiment Construction

[0024] With reference to accompanying drawing, the video super-resolution method based on compressed domain of the present invention, carries out in the following steps:

[0025] 1. Unzip

[0026] First, the input low-resolution compressed video is decompressed to obtain low-resolution video images, quantization matrices, quantized transform domain coefficients, motion-compensated predicted video images, and motion vectors.

[0027] 2. Modeling the process from natural scene to compressed video

[0028] Establish the relationship between low-resolution images and corresponding high-resolution images: High-resolution images are blurred / downsampled / compressed / decompressed to obtain low-resolution images. Remember the lth frame of low-resolution image after decompression is y l , the corresponding high-resolution image is f l , the fuzzy function is H, the downsampling matrix is ​​A, and the quantization noise in the process is denoted as ε Q，l , then y l =AHf l +ε Q，l . ...

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Abstract

The invention discloses a video super-resolution method applicable to a compressed domain, which fully utilizes the information of a plurality of previous and next frames for the purpose of the super-resolution reconstruction of a target frame. The method mainly comprises the following steps of: firstly, uncompressing a low-resolution video to obtain various information; then respectively obtaining various single super-resolution images in a current window by using the obtained information and a Bayesian framework; and finally, reconstructing a final super-resolution image of the target frameby utilizing the single super-resolution images in the current window. During such processes, the method provides a gradient distribution that the gradient distribution of the super-resolution image is as close as practicable to uncompressed low-resolution images, and takes the provided gradient distribution as prior probability; and the method utilizes IRLS to construct a target function, therebyweakening the influence from outliers and noise, leading the obtained super-resolution image to be higher in PSNR, introducing little new noise and inhibiting coding noise and ringing effect. By sequentially sliding mobile windows, a super-resolution video can be obtained.

Description

Technical field: [0001] The invention relates to a video super-resolution method applicable to a compressed domain. The obtained super-resolution image maintains clear borders and suppresses coding noise and "ringing" effects at the same time. This method makes full use of the information in the compressed code stream, and solves the problems of calibration, interpolation, restoration and post-processing at the same time. Can be applied to compressed video in various MPEG4 formats. Background technique: [0002] Due to the limitations of imaging equipment itself, data compression algorithms, and transmission errors, the video image resolution that can be obtained in practical applications often cannot meet the high-definition requirements. In order to solve this problem, people have proposed a super-resolution algorithm for sequence images, which reconstructs a single image with better quality and higher resolution from multiple images with poorer quality and lower resoluti...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N7/26H04N7/50H04N19/186
Inventor 张小红童若峰
Owner ZHEJIANG UNIV
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