Adaptive compressive sensing image coding method based on measurement domain saliency detection model
A detection model and compressed sensing technology, applied in the field of image coding, can solve the problems of rate-distortion performance increasing coding complexity, unfavorable wireless sensor network applications, etc., to achieve the effect of improving reconstruction quality and high-rate-distortion performance
Active Publication Date: 2018-09-25
XINYANG NORMAL UNIVERSITY
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However, the above-mentioned adaptive measurement methods all use full-sampled images to extract features, and the amount of calculation introduced may be equivalent to that of full transformation. The rate-distortion performance is improved at the cost of increased coding complexity, which is not conducive to the application in wireless sensor networks.
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[0056] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0057] The block diagram of the low-complexity compressed sensing image encoding and decoding proposed by the present invention is as follows: figure 1 shown. Set the total image measurement rate S, and determine the total measurement times M as
[0058] M=N·S (1)
[0059] On the encoding side, first, the scene is compressed by the imaging device with size I r × I c (N=I r ·I c ) Each block in the image x of ) implements pre-measurement, that is, the preset initial measurement times are as follows:
[0060]
[0061] round[·] is the rounding operator. Divide the image x into n blocks of size B×B, where B is 16, and the i-th image block is recorded as a column vector form x i (i=1, 2,..., n, n=N / B 2 ), the generated size is M 0 ×B 2 The Gaussian random measurement matrix Φ B0 , the calculated length is M 0 The in...
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The invention discloses an adaptive compressive sensing image coding method based on a measurement domain saliency detection model. The method comprises steps of (1) diving an input image into multiple image blocks which are not overlapped with each other; (2) setting the initial measurement times M0, constructing an initial block measurement matrix, implementing pre-measurement on each block andacquiring the initial measurement vector y0i of each block; (3) by use of the initial measurement vector y0i of each block, implementing saliency detection in a measurement domain, and calculating thesaliency degree wi of each block; (4) according to the distribution of the saliency degrees of the blocks, adaptively setting the measurement times M1 of each block, constructing a block measurementmatrix according to the measurement times of each block and carrying out compressive sensing measurement block by block; and (5) weighting target functions of an image reconstruction model based on the block saliency, establishing an adaptive global reconstruction model, optimizing a high saliency region in a centralized manner and generating a final reconstruction image. According to the invention, objective and subjective reconstruction quality of the image can be effectively improved; and for the whole performance, compared with the prior art, quite good improvement of rate-distortion performance is achieved.
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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, it proposes realizing saliency detection in a measurement domain, and implementing compressed sensing measurement adaptively to saliency information, so as to improve the rate-distortion performance of image coding. Background technique [0002] In wireless sensor networks, the energy consumption and bandwidth of image sensor nodes are greatly limited. However, traditional image coding techniques (such as JPEG) are based on the transform coding framework, which needs to introduce a large amount of calculation to implement a full transformation of the image. Therefore, the traditional Image encoding will greatly reduce the life cycle of image sensing nodes. In order to prolong the life cycle of image sensing nodes in wireless sensor networks, a new low-complexity image coding technique needs to be found....
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IPC IPC(8): G06T9/00
CPCG06T9/00H04N19/147
Inventor 李然刘宏兵刘正辉
Owner XINYANG NORMAL UNIVERSITY