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Multiple transform domain based super-resolution reconstruction method

A technology of super-resolution reconstruction and multiple transformations, which is applied in image analysis, graphic image conversion, image data processing, etc., and can solve problems such as fuzzy, inaccurate, and distortion of remote sensing images

Active Publication Date: 2016-05-04
CHINA ACADEMY OF SPACE TECHNOLOGY
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Problems solved by technology

[0005] The purpose of the present invention is to address the deficiencies in the prior art and provide a super-resolution reconstruction method based on multiple transform domains. This method utilizes the reconstruction method of compressed sensing to solve the super-resolution reconstruction problem, so as to overcome the problems of existing remote sensing images. Blurring, imprecise, and distortion issues

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Embodiment Construction

[0038] Embodiments of the present invention will now be described in detail with reference to the method of the present invention in conjunction with the accompanying drawings. Such as figure 2 As shown, the steps of the super-resolution reconstruction method of the present invention are as follows:

[0039] The first step is to obtain multiple low-resolution images g that require super-resolution reconstruction 1 , g 2 ,...,g k , and select a low-resolution image g ref as a reference image.

[0040] In the second step, the registration mapping matrix M is obtained by the method of elastic registration 1 , M 2 ,...,M k , the elastic registration method overcomes the irregular geometric distortion and dislocation caused by the load platform shake and atmospheric disturbance.

[0041] The elastic registration can use any current method that can overcome irregular geometric distortion and dislocation, such as an elastic registration method proposed by S.Periaswamy and H....

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Abstract

The invention relates to a multiple transform domain based super-resolution reconstruction method and belongs to the technical field of image super-resolution. The method comprises the following steps: performing nonrelated transform domain analysis on K input low-resolution images separately; according to the sizes of a target super-resolution image and the input low-resolution images, determining a down-sampling matrix D; and reconstructing the super-resolution image by adopting an optimization algorithm for L1-norm minimization in multiple transform domains through the constraint of a cost function min lambda1||W1(z1)||1+lambda2||W2(z2)||2+......+lambdaj||Wj(zj)||1 by z=z1+z2+...+zj and ||DHiMiz-gi||2<=ni (i=1,2,...K). Compared with the prior art, the method solves the problem in selection of a priori probability model in super-resolution reconstruction, namely, multiple transform domain based remote sensing image sparsity expression; and meanwhile, the method solves the problems of irregular geometric distortion and dislocation of low-resolution remote sensing images caused by load platform shake and atmospheric disturbance, and reconstructs the super-resolution image with a good effect.

Description

technical field [0001] The present invention relates to a super-resolution reconstruction method, in particular to a super-resolution reconstruction method based on multiple transformation domains, that is, to reconstruct a high-resolution image by using multi-temporal low-resolution images of the same scene in a post-processing manner The method belongs to the technical field of image super-resolution. Background technique [0002] High-resolution imaging is of great significance to many aspects such as remote sensing, military affairs, astronomy, and biomedicine. The human pursuit of high-resolution images has never stopped. Due to the limitations of imaging equipment in theory and objective conditions, the spatial resolution of imaging often encounters bottlenecks. For example, when other conditions remain unchanged, the most direct way to improve resolution is to increase the density of CCD or CMOS, that is, to reduce the size of each photosensitive unit. However, when ...

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Application Information

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IPC IPC(8): G06T3/40
CPCG06T3/4053G06T2207/10032G06T2207/20064
Inventor 李峰辛蕾詹锟刘露
Owner CHINA ACADEMY OF SPACE TECHNOLOGY
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