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

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...

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