Gradient contour example dictionary and weighted adaptive p norm-based single image super-resolution reconstruction method

A technology of super-resolution reconstruction and gradient contour, which is applied in image analysis, image enhancement, image data processing, etc., can solve the problem that the performance is highly dependent on the similarity between training set and test set

Inactive Publication Date: 2018-09-14
XIHUA UNIV
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Problems solved by technology

Learning-based methods can recover image details well, but the performance is highly dependent on the similarity between the training set and the test set

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  • Gradient contour example dictionary and weighted adaptive p norm-based single image super-resolution reconstruction method
  • Gradient contour example dictionary and weighted adaptive p norm-based single image super-resolution reconstruction method
  • Gradient contour example dictionary and weighted adaptive p norm-based single image super-resolution reconstruction method

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Embodiment Construction

[0017] The present invention will be further described below in conjunction with accompanying drawing:

[0018] figure 1 , based on gradient contour example dictionaries and weighted adaptive p A single image super-resolution reconstruction method of norm, comprising the following steps:

[0019] (1) For the input low-resolution image, use the bicubic interpolation method to upsample to obtain the initial high-resolution estimated image;

[0020] (2) The estimation of the high-resolution gradient image is completed by the neighborhood embedding super-resolution reconstruction method based on the gradient profile example dictionary, and the estimated high-resolution gradient image is used to construct the gradient domain prior;

[0021] (3) According to the existing high-resolution estimated image, extract the adaptive neighborhood of each reference pixel, and perform non-local similar block search to form a shape-adaptive similar block group;

[0022] (4) According to the e...

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Abstract

The invention discloses a gradient contour example dictionary and weighted adaptive p norm-based single image super-resolution reconstruction method, which mainly comprises the following steps: performing up sampling on an input low-resolution image by using an interpolation method; completing estimation of a high-resolution gradient image through a gradient contour example dictionary-based neighbor embedding super-resolution reconstruction method; constructing a shape-adaptive similar block group; constructing a weighted p norm restriction of a singular value of the shape-adaptive similar block group, and adaptively adjusting a p value restricted by a norm of each similar block group according to the significance of an image region; constructing a reconstruction cost function, and performing iterative optimization solving to obtain a finally output high-resolutio image. The gradient contour example dictionary and weighted adaptive p norm-based single image super-resolution reconstruction method disclosed by the invention is relatively good in subject perception and relatively high in objective evaluation value. Therefore the invention is an effective single image super-resolutionreconstruction method.

Description

technical field [0001] The present invention relates to image super-resolution reconstruction technology, in particular to a gradient profile example dictionary and weighted self-adaptive p The invention discloses a norm single image super-resolution reconstruction method, which belongs to the field of digital image processing. Background technique [0002] In real life, limited by factors such as imaging system hardware equipment, imaging conditions, and information transmission conditions, people often cannot obtain high-resolution observation images. Image super-resolution reconstruction technology can break through these constraints without increasing hardware costs, and use one or more low-resolution observation images with complementary information to reconstruct a high-resolution image, enabling people to Can better understand the image content and make further analysis and utilization. Compared with multi-image super-resolution technology, single-image super-reso...

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Application Information

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IPC IPC(8): G06T3/40G06T7/13G06T5/00
CPCG06T3/4007G06T3/4053G06T7/13G06T5/73G06T5/70
Inventor 李滔董秀成
Owner XIHUA UNIV
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