Enhancing Denoised Image Via Fusion with a Noisy Image

Jun Sang Yoo, Jong Ok Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Image denoising unintendedly removes the original information as well as noises. Especially, texture tends to be easily distorted and smoothed by denoising because it is not distinguishable from noise. In this paper, we propose a novel framework to enhance the denoised image. The lost information of the denoised image is restored by fusing it with a noisy input. The proposed fusion is done by cost optimization which includes two data terms (noisy and denoised), and sparsity constraint term which is adopted to effectively suppress the noise in the principal component analysis (PCA) domain. The fusing weight between noisy and denoised significantly depends on the local region characteristics. PCA coefficient and eigenvector are estimated in a alternate way, and are used for estimating the enhanced version. Experimental results show that the proposed method convincingly improve texture and structural information for an image.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Image Processing, ICIP 2019 - Proceedings
PublisherIEEE Computer Society
Pages1790-1794
Number of pages5
ISBN (Electronic)9781538662496
DOIs
Publication statusPublished - 2019 Sept
Event26th IEEE International Conference on Image Processing, ICIP 2019 - Taipei, Taiwan, Province of China
Duration: 2019 Sept 222019 Sept 25

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2019-September
ISSN (Print)1522-4880

Conference

Conference26th IEEE International Conference on Image Processing, ICIP 2019
Country/TerritoryTaiwan, Province of China
CityTaipei
Period19/9/2219/9/25

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

  • Image denoising
  • PCA
  • cost optimization
  • sparsity
  • texture

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

Fingerprint

Dive into the research topics of 'Enhancing Denoised Image Via Fusion with a Noisy Image'. Together they form a unique fingerprint.

Cite this