Support set and signal value detection based video compressive sensing reconstruction method

A technology of video compression and support set, which is applied in the fields of digital video signal modification, image communication, electrical components, etc. It can solve the problems of low reconstruction quality, slow speed, and low reconstruction quality.

Active Publication Date: 2014-10-29
XIDIAN UNIV
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Problems solved by technology

At present, for the optimal solution of convex problems, Stephen Boyd of Stanford University and others proposed an alternating direction multiplier method ADMM. Although this method requires a relatively small number of measurements, it is slow and the reconstruction quality is relatively low.
In addition, Y.Wang and

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  • Support set and signal value detection based video compressive sensing reconstruction method
  • Support set and signal value detection based video compressive sensing reconstruction method
  • Support set and signal value detection based video compressive sensing reconstruction method

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Embodiment Construction

[0046] Below in conjunction with accompanying drawing, technical scheme of the present invention and effect are described in further detail:

[0047] refer to figure 1 , the implementation steps of the present invention are as follows:

[0048] Step 1, video sequence grouping

[0049] The video image sequence is divided into image groups GOP, that is, the continuous L frames of the video image sequence are divided into one group, the first frame of each group is used as a reference frame, and the remaining L-1 frames are used as non-reference frames, where L is greater than or equal to The natural number of 2.

[0050] Step 2, block processing

[0051] The reference frames and non-reference frames in each group of video images are divided into n non-overlapping two-dimensional macroblocks B with a size of N×N, where N is a positive integer.

[0052] Step 3, compressed sensing sampling

[0053] (3a) Use the randn function in matlab to generate an orthogonal Gaussian random...

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Abstract

The invention discloses a support set and signal value detection based video compressive sensing reconstruction method which mainly solves the problem of poor reconstructed image quality in the prior art. The method includes the implementation steps: (1) dividing a video sequence into reference frames and non-reference frames according to image groups; (2) dividing the reference frames and non-reference frames into non-overlapping macro blocks identical in size; (3) subjecting all the macro blocks to compressive sensing measurement; (4) utilizing measurement values as input and updating iteration variables of a reconstructed image; (6) updating a support set and a signal detection value according to updated iteration variables of the reconstructed image; (7) computing a residual error of the reconstructed image according to the signal detection value; (8) judging whether iteration is terminated or not according to constraint conditions of the residual error of the reconstructed image; (9) outputting a reconstructed image signal. The support set and signal value detection based video compressive sensing reconstruction method can improve reconstructed image quality effectively and can be utilized for video image processing.

Description

technical field [0001] The invention belongs to the field of video image processing, relates to a video compression perception reconstruction method, and can be used for video image processing. Background technique [0002] In recent years, with the rapid development of digital signal processing technology, the amount of data to be processed is increasing at an alarming rate. The traditional Nyquist sampling theorem requires that the sampling frequency of the signal should not be lower than twice the maximum frequency of the signal. Higher requirements are put forward for hardware devices with limited signal processing capabilities. In order to break through the traditional signal processing method based on Nyquist sampling theory, a new type of compressed sensing that combines data acquisition and data compression processes into one Theory has become one of the hot spots of research at home and abroad. [0003] The traditional Nyquist theory is suitable for bandwidth-limit...

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Application Information

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IPC IPC(8): H04N19/132H04N19/177H04N19/63
Inventor 田方宋彬魏正刘海啸李莹华
Owner XIDIAN UNIV
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