research-article

Research on image denoising algorithm based on non-local block matching

Authors:

Ying Yang,

Dongrui Li,

Xiaofeng HuangAuthors Info & Claims

International Journal of Information and Communication Technology, Volume 16, Issue 3

Pages 245 - 260

https://doi.org/10.1504/ijict.2020.106317

Published: 01 January 2020 Publication History

Abstract

In order to study how to better suppress image noise, improve image resolution, and enhance the visual effect of images, three-dimensional joint filtering – block matching (BM3D) algorithm is used to explore image denoising and image detail retention, and in image denoising, sparse expression and low rank recovery theory are introduced. The results show that BM3D algorithm has a good effect in removing Gaussian white noise, but it is lacking in suppressing impulse noise and mixed noise. The non-local BM3D algorithm is superior to sparse expression and low rank recovery in removing Gaussian white noise, but sparse expression and low rank recovery has a good effect in removing impulse noise.

Index Terms

Research on image denoising algorithm based on non-local block matching
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
  2. Computer graphics
    1. Image manipulation

Index terms have been assigned to the content through auto-classification.

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Published In

International Journal of Information and Communication Technology Volume 16, Issue 3

2020

93 pages

ISSN:1466-6642

EISSN:1741-8070

DOI:10.1504/ijict.2020.16.issue-3

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Inderscience Publishers

Geneva 15, Switzerland

Publication History

Published: 01 January 2020

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Image Denoising with Signal Dependent Noise Using Block Matching and 3D Filtering

A New Adaptive TV-Based BM3D Algorithm for Image Denoising

MOTF: Multi-objective Optimal Trilateral Filtering based partial moving frame algorithm for image denoising

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