Back to Search Start Over

MULTIPARENT FRACTAL IMAGE CODING-BASED METHODS FOR SALT-AND-PEPPER NOISE REMOVAL.

Authors :
LIANG, WEIJIE
LI, XIAOYI
TU, ZHIHUI
LU, JIAN
Source :
Fractals. 2024, Vol. 32 Issue 1, p1-15. 15p.
Publication Year :
2024

Abstract

Salt-and-pepper noise consists of outlier pixel values which significantly impair image structure and quality. Multiparent fractal image coding (MFIC) methods substantially exploit image redundancy by utilizing multiple domain blocks to approximate the range block, partially compensating for the information loss caused by noise. Motivated by this, we propose two novel image restoration methods based on MFIC to remove salt-and-pepper noise. The first method integrates Huber M-estimation into MFIC, resulting in an improved anti-salt-and-pepper noise robust fractal coding approach. The second method incorporates MFIC into a total variation (TV) regularization model, including a data fidelity term, an MFIC term and a TV regularization term. An alternative iterative method based on proximity operator is developed to effectively solve the proposed model. Experimental results demonstrate that these two proposed approaches achieve significantly enhanced performance compared to traditional fractal coding methods. [ABSTRACT FROM AUTHOR]

Subjects

Subjects :
*IMAGE reconstruction

Details

Language :
English
ISSN :
0218348X
Volume :
32
Issue :
1
Database :
Academic Search Index
Journal :
Fractals
Publication Type :
Academic Journal
Accession number :
175445527
Full Text :
https://doi.org/10.1142/S0218348X24500129