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Super-resolution Image Reconstruction Method Based on Gradient Consistency and Anisotropy Regularization

A super-resolution image, anisotropic technology, applied in the field of image processing, can solve the problems of seldom considering the adaptability of gradient recovery, and the super-resolution image is not natural enough.

Inactive Publication Date: 2016-03-02
XIDIAN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, in current methods of this kind, the adaptability of gradient restoration is rarely considered, and the low-frequency image information and high-frequency image information are processed under a unified framework, and the restored super-resolution image is not natural enough.

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  • Super-resolution Image Reconstruction Method Based on Gradient Consistency and Anisotropy Regularization
  • Super-resolution Image Reconstruction Method Based on Gradient Consistency and Anisotropy Regularization
  • Super-resolution Image Reconstruction Method Based on Gradient Consistency and Anisotropy Regularization

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Embodiment Construction

[0024] The specific realization and effect of the present invention are described in further detail below with reference to the accompanying drawings:

[0025] refer to figure 1 , the known low-resolution image L and the point spread function f, where f takes a Gaussian blur kernel with a size of 13x13 and a variance of 1. Set parameters, when magnified by 2 times: k 1 =15,k 2 =-0.01,k 3 =0.3, T=42; when magnified by 3 times: k 1 =15,k 2 =-0.03,k 3 =1.4, T=42; when magnified by 4 times: k 1 =15,k 2 =-0.03,k 3 =1.4, T=42. The target image H can be obtained by the following steps * . Implementation steps of the present invention are as follows:

[0026] Step 1: Input a known low-resolution image L, and use the bicubic interpolation method to upsample the input image L to obtain an interpolated image

[0027] Step 2, get the interpolated image from step 1 Take the point spread function f as a Gaussian blur kernel with a size of 13x13 and a variance of 1, and perf...

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Abstract

The invention discloses a super resolution image reconstruction method based on gradient consistency and anisotropic regularization. The super resolution image reconstruction method based on the gradient consistency and the anisotropic regularization is used for solving super resolution image reconstruction self-adaption to maintain high-frequency image information, and recovering image detail information. The steps includes inputting a low resolution image, obtaining an interpolation image by using dual-three interpolation methods to sample the input image, adopting gradient consistency and anisotropic regularization (GCAR) conditions to restrain an objective function, performing a deconvolution operation for the interpolation image, judging a deconvoluted image whether to meet output requirements, outputting a super resolution result if the deconvoluted image meets the output requirements, otherwise, performing reconvuluting and pixel replacement for the deconvoluted image, going to a next deconvolution operation, and iterating like those until the output requirements are met. The super resolution image reconstruction method based on the gradient consistency and the anisotropic regularization has the advantages of maintaining the gradient consistency of low contrast image area low resolution images and corresponding high resolution images, and capable of recovering image detail information in a self-adaption mode and being used for the field of video applications.

Description

technical field [0001] The invention belongs to the field of image processing, in particular to a super-resolution image reconstruction method based on gradient consistency and anisotropy regularization, which can be used for problems in the field of video and image applications. Background technique [0002] Image super-resolution is one of the most basic problems in computer vision and digital image processing, and it is the basis for further analysis and recognition of images. Image superresolution (superresolution, SR) refers to recovering a high resolution image (high resolution, HR) from a low resolution image (low resolution, LR) or image sequence. High resolution image (high resolution, HR) means that the image has high pixel density, which can provide more details, which often play a key role in the application. Its purpose is to restore the detailed information of the image. At the same time, it is of great significance to study image super-resolution, which can ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00G06T3/40
Inventor 郑喆坤焦李成谷爱国孙增增鞠军委王帅施舒楠马文萍马晶晶
Owner XIDIAN UNIV
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