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Moiré Elimination Method of Fabric Image Based on Low Rank Sparse Matrix Decomposition

A technology of sparse matrix and moiré, applied in image enhancement, image data processing, instruments, etc.

Active Publication Date: 2018-05-08
TIANJIN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

The technical solution adopted by the present invention is to construct a low-rank sparse matrix decomposition model by using the local self-similarity of fabric texture and the energy concentration and distribution characteristics of moiré in the frequency domain based on the low-rank sparse matrix decomposition method for eliminating moiré in fabric images. Solve the problem of eliminating moiré in fabric images by separating the fabric texture from the moiré pattern

Method used

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  • Moiré Elimination Method of Fabric Image Based on Low Rank Sparse Matrix Decomposition
  • Moiré Elimination Method of Fabric Image Based on Low Rank Sparse Matrix Decomposition
  • Moiré Elimination Method of Fabric Image Based on Low Rank Sparse Matrix Decomposition

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Embodiment Construction

[0080] The method for eliminating moiré in fabric images based on low-rank sparse matrix decomposition of the present invention will be described in detail below in conjunction with the embodiments and accompanying drawings.

[0081] The invention adopts a low-rank sparse matrix decomposition model to remove the moiré pattern of the fabric image: the problem of eliminating the moiré pattern in the fabric image is attributed to the image segmentation problem, and the local self-similarity of the fabric texture and the energy concentration distribution of the moiré pattern in the frequency domain are used characteristics, build a low-rank sparse matrix factorization model, and separate the fabric texture from the moiré pattern; by constraining the distribution of the moiré pattern in the frequency domain, the separation performance of the fabric texture and the moiré pattern is improved to avoid the folds and moiré patterns in the fabric image. Edges, shadows, etc. are misjudged ...

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Abstract

The invention belongs to the digital image processing field and is for eliminating mole stripe patterns in fabric images. The fabric image mole stripe elimination method based on low-rank sparse matrix decomposition is characterized in that, local self-similarity of fabric textures and energy concentration distribution characteristics of the mole stripe in a frequency domain are utilized, a low rank sparse matrix decomposition model is constructed, the fabric textures are separated from the mole stripe pattern, and thereby a problem of mole stripes in the fabric image can be solved. The fabric image mole stripe elimination method based on low-rank sparse matrix decomposition is mainly applied to digital image processing.

Description

technical field [0001] The invention belongs to the field of digital image processing, and in particular relates to a method for eliminating moiré patterns of fabric images based on low-rank sparse matrix decomposition. Background technique [0002] The moiré phenomenon is very easy to appear in the modern digital imaging process, such as: scanner scanning halftone prints, digital cameras shooting screens or scenes containing regular patterns (cloth patterns on clothes, windows or grids on buildings). Moiré patterns often have a large area in the image, and the color shift is obvious, which seriously affects the image quality and image analysis results, and has attracted widespread attention. [0003] So far, image moiré removal algorithms have mainly targeted halftone scanned images. Among various image moiré patterns, the moiré pattern in halftone images is a relatively simple type of moiré pattern, and its shape, distribution, etc. are closely related to the printer equi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
Inventor 杨敬钰张雪刘芳蕾
Owner TIANJIN UNIV
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