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A Low Complexity Compressive Sensing Image Coding Method with Adaptive Texture Contrast

A compressed sensing and image coding technology, applied in the field of image coding, can solve the problems of ignoring high-frequency texture details and unsatisfactory restoration effect, and achieve the effect of improving reconstruction quality and high rate distortion performance

Inactive Publication Date: 2019-05-31
XINYANG NORMAL UNIVERSITY
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Problems solved by technology

Block variance and image edge adaptive measurement are common means in the existing adaptive measurement rate setting methods, but they only protect the low-frequency information in the image during the measurement process, while ignoring the high-frequency information that the human eye is more interested in. Texture details, resulting in unsatisfactory restoration effect

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  • A Low Complexity Compressive Sensing Image Coding Method with Adaptive Texture Contrast
  • A Low Complexity Compressive Sensing Image Coding Method with Adaptive Texture Contrast
  • A Low Complexity Compressive Sensing Image Coding Method with Adaptive Texture Contrast

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Embodiment Construction

[0054] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0055] The block diagram of the low-complexity compressed sensing image encoding and decoding proposed by the present invention is shown in FIG. 1 . On the encoding side, first, the scene is fully sampled by the CMOS sensor to generate a size I r × I c (N=I r · I c ) image x, then divide the image x into n blocks of size B×B, where B is 8, and the i-th image block is recorded as a column vector form x i (i=1, 2,..., n, n=N / B 2 ), and then calculate the number of measurements M of each block according to the block texture contrast i (2 ), generating the corresponding random measurement matrix Φ Bi , and finally, the length M is obtained from formula (1) B (2 ) of each block measurement vector y i as follows:

[0056] the y i = Φ Bi x i (1)

[0057] where Φ Bi is M B ×B 2 The random Gaussian matrix of , addition...

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Abstract

The invention discloses a low-complexity compressive sensing image coding method adapted to texture contrast. The method comprises the steps of: (1) dividing an input image into a plurality of non-overlapped image blocks; (2) utilizing a maximum gradient in a pixel eight communication regions to measure the texture change degree of each pixel in the input image, and generating a texture characteristic graph; (3) utilizing the texture characteristic graph to calculate the texture contrast of each block, based on the texture contrast, setting a measuring rate of each block in an adapted manner, constructing a block measuring matrix according to the measuring rate of each block, and carrying out compressive sensing measurement block by block; and (4) establishing an adapted global reconstruction model with a target function of a block texture contrast weighted image reconstruction model, carrying out centralized optimization on a texture-enriched region, and generating a final reconstruction image. According to the invention, the subjective and objective reconstruction quality of the image is effectively improved, and compared with the prior art, the rate-distortion performance is greatly improved.

Description

technical field [0001] The invention belongs to the technical field of image coding, and relates to a low-complexity coding method based on compressed sensing, in particular, a compressed sensing measurement method adaptive to image texture contrast distribution is proposed to improve the rate-distortion performance of image coding. Background technique [0002] Traditional image coding (such as JPEG) takes image transformation as the core, and is based on the Nyquist frequency-domain sampling theorem. It requires the number of image transformations to be at least the total number of pixels in the image to restore the image accurately. However, in wireless sensor network terminals with limited computing power and power consumption, too many transformations will introduce high computational complexity, which makes traditional image coding unsuitable for "light" acquisition points. In addition, traditional image coding implements a full transformation of the image, causing inf...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T9/00
CPCG06T9/001
Inventor 李然刘正辉马文鹏刘宏兵
Owner XINYANG NORMAL UNIVERSITY