Multi-view compressed sensing image reconstruction method

A compressed sensing, multi-view technology, applied in the field of image coding, which can solve the problem that the spatial characteristics of the image cannot be used.

Active Publication Date: 2013-09-11
RUNJIAN COMM
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However, the method of residual reconstruction cannot take advantage of the spatial characteristics of the image itself, and the performance of this method still has room for improvement
[0008] In summary, at the receiving end, in

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[0034] In order to make the purpose, technical means and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings.

[0035] In order to solve the problems existing in the prior art, the present invention proposes a brand-new multi-view compressed sensing image reconstruction method, that is, at the receiving end, the correlation of images from different views and the spatial characteristics of the same view image are used to establish a joint reconstruction problem. And the established joint reconstruction problem is decomposed into a method of alternate iterative resolving of perspective reconstruction image and residual image. First, traditional methods are used to solve the TV norm minimization problem, and the images are reconstructed independently. Second, block-based DE and DC operations are performed between the reconstructed images to obtain predicted images for each v...

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Abstract

The invention discloses a multi-view compressed sensing image reconstruction method. The multi-view compressed sensing image reconstruction method includes: receiving measured values of various view-angle images at a receiving end and independently reconstructing various view-angle images; performing DE (disparity estimation) and DC (disparity compensation) on the basis of blocks among the reconstructed images and acquiring predicted images of each view angle; solving a joint reconstruction problem set for each view angle by means of the predicted images and the measured values and determining the final reconstruction images of various view angles. In the set joint reconstruction problem, not only can sparsity characteristics of residual errors between the view-angle images and the predicted images in a transform domain be taken into consideration, but the sparsity characteristics of the view-angle images in the transform domain is further considered. Meanwhile, the joint reconstruction problem is solved into an alternative iteration problem of view-angle reconstruction images and residual-error images and can be solved by multiple times of iteration. By the multi-view compressed sensing image reconstruction method, performance and effect of the image reconstruction can be effectively improved.

Description

technical field [0001] The present application relates to image coding technology, in particular to a method for reconstructing multi-view compressed sensing images in the image coding technology. Background technique [0002] Compressed Sensing (CS) is an emerging theoretical system that has received extensive attention in the field of signal processing in recent years. The theory states that if a signal to be sampled is sparse (or sparse in a transform domain), then the possibility of accurately recovering the original signal from its limited uncorrelated measurements is extremely high. The introduction of CS theory has greatly enriched and developed the signal acquisition theory, and provided new technologies and new ideas for research in other related fields. Because the computational complexity of the measurement process of CS is low, and the reconstruction process needs to iteratively solve a relatively high-complexity optimization problem, its theoretical structure i...

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Application Information

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IPC IPC(8): G06T11/00
Inventor 覃团发常侃
Owner RUNJIAN COMM
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