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Image interpolation system and image interpolation method based on adaptive low-rank regularization

An adaptive, intra-image technology, applied in image enhancement, image data processing, instruments, etc., can solve problems such as difficult to find similar image blocks, low rank, etc.

Inactive Publication Date: 2015-07-22
SOUTH CENTRAL UNIVERSITY FOR NATIONALITIES
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] However, for image blocks with rich texture information, it is difficult to find a sufficient number of similar image blocks to have good low-rank performance

Method used

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  • Image interpolation system and image interpolation method based on adaptive low-rank regularization
  • Image interpolation system and image interpolation method based on adaptive low-rank regularization
  • Image interpolation system and image interpolation method based on adaptive low-rank regularization

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Embodiment Construction

[0052] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0053] see figure 1 As shown, the embodiment of the present invention provides an image interpolation system based on adaptive low-rank regularization, including an initialization module 1, a route selection module 2, an image filtering module 3 and a regularized minimum mean square error inversion module 4, and the image The filtering module 3 includes an image overlapping block unit 301, an image block group generation unit 302, an image block smoothness detection unit 303, an image block group adaptive low-rank decomposition unit 304, and an image block group averaging unit 305, wherein: the routing selection module 2 There are two input terminals and one output terminal. The image block group generation unit 302 has one input terminal and two output terminals. The image block group adaptive low-rank decomposition unit 304 has two ...

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Abstract

The invention discloses an image interpolation system and an image interpolation method based on adaptive low-rank regularization, and relates to the technical field of image super-resolution. The image interpolation system and the image interpolation method has the advantages that missed pixels are calculated from known local neighborhoods through polynomial approximation according to similarity between adjacent image pixels by a classical bi-cubic method to acquire an initial value of an interpolated high-resolution image; quality of the high-resolution image is improved effectively through repeated iterative optimization; each iteration includes two processes, the first process includes filtering an acquired high-resolution image estimation by an adaptive matrix low-rank decomposition technique, and the second process includes updating the estimated high-resolution image according to a known low-resolution image and a filtering result, acquired from the first process, of the high-resolution image estimation by a regulated minimum mean square error inversion technique. The image interpolation system and the image interpolation method have low calculation complexity and can effectively improve quality of the interpolated image.

Description

technical field [0001] The invention relates to the technical field of image super-resolution, in particular to an image interpolation system and method based on adaptive low-rank regularization. Background technique [0002] Image super-resolution aims to restore high-resolution images from low-resolution images, and it has a wide range of applications in medical imaging, digital photography, and computer vision. Image interpolation is a special case of image super-resolution, where low-resolution images are assumed to be the result of direct downsampling of high-resolution images. Image interpolation is the inverse process of image downsampling, which is a typical ill-conditioned problem. In order to obtain high-quality high-resolution images through interpolation, basic assumptions and prior knowledge about images are essential. For example, classical linear interpolation methods such as bi-linear interpolation and bi-cubic interpolation use polynomial approximations to...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
Inventor 高志荣熊承义丁立新
Owner SOUTH CENTRAL UNIVERSITY FOR NATIONALITIES
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