Video image compressed sensing reconstruction method based on partition strategy and genetic evolution

A technology of compressive sensing reconstruction and video image, which is applied in the field of image and video processing, can solve the problems of unsatisfactory reconstruction effect and blurred edges of motion, etc., and achieve the effect of reducing sampling rate and good reconstruction effect

Inactive Publication Date: 2016-05-11
XIDIAN UNIV
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Problems solved by technology

This method reconstructs the time-compressed video sequence by establishing a Gaussian mixture model for the spatio-temporal video block, and obtains a good reconstruction effect. The partial reconstruction effect of the frame change is not very ideal, and the edge part of the motion is blurred

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  • Video image compressed sensing reconstruction method based on partition strategy and genetic evolution
  • Video image compressed sensing reconstruction method based on partition strategy and genetic evolution
  • Video image compressed sensing reconstruction method based on partition strategy and genetic evolution

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Embodiment Construction

[0020] The present invention will be further described below in conjunction with the accompanying drawings.

[0021] Refer to attached figure 1 , the concrete steps of the present invention are as follows:

[0022] Step 1. Acquisition of observation vectors.

[0023] Input a video of size 256×256×96. Taking 8 frames as a group, each frame of the video image is divided into 8×8 blocks. The image blocks are divided into non-changing blocks and changing blocks according to the bi-norm of difference values ​​of image blocks at the same position in adjacent frames. For non-changing blocks, random Gaussian observations are only made on the non-changing image blocks of the first frame of each group of video, and no observation is required on non-changing image blocks of other video frames; corresponding Gaussian random observations are performed on all changing blocks of each group of videos Observation; the observation rate of the non-changing block and the changing block is dif...

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Abstract

The invention discloses a video image compressed sensing reconstruction method based on a partition strategy and genetic evolution, and mainly aims to solve the problem of fuzzy reconstruction effect of changed parts in previous and next frames of a video in the prior art. According to the implementation scheme, the method comprises the following steps: 1, acquiring observation vectors, and partitioning frames of images in a video image by taking eight frames as one group; 2, dividing the image blocks into changed blocks and unchanged block according to 2-norms of difference values between adjacent frames at the same positions, performing Gaussian observation on all the changed blocks, and performing Gaussian observation on every group of first-frame image blocks in the unchanged blocks; 3, performing image block structure discrimination on observation vectors of a transmitter; 4, extracting the observation vectors with the same image block structures to perform AP clustering; and 5, performing group initialization according to classes of every class of image blocks based on a redundant dictionary, and performing genetic optimization reconstruction on data through crossover, variation based on directional statistics and operator selection. Through adoption of the method, the changed parts in the previous and next frames of the video can be reconstructed well. The method can be applied to reconstruction of natural image videos.

Description

technical field [0001] The invention belongs to the technical field of image and video processing, and further relates to a video compression sensing reconstruction method, which can be used to reconstruct natural image video sequences. Background technique [0002] In recent years, a new data theory compressive sensing CS has emerged in the field of signal processing. This theory realizes compression while collecting data, breaks through the limitations of the traditional Nyquist sampling theorem, and brings new advantages to data collection technology. The revolutionary changes make the theory have broad application prospects in compressed imaging systems, military cryptography, wireless sensing and other fields. Compressed sensing theory mainly includes three aspects: sparse representation of signal, observation of signal and reconstruction of signal. Among them, designing a fast and effective reconstruction algorithm is an important part of successfully promoting and ap...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T9/00G06N3/12H04N5/14
CPCG06T9/00G06N3/126H04N5/144
Inventor 刘芳李婷婷程晓东郝红侠焦李成尚荣华马文萍马晶晶杨淑媛
Owner XIDIAN UNIV
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