&lt;title&gt;Image restoration by multiscale entropy&lt;/title&gt;

Jean‐Luc Starck

doi:10.1117/12.366843

ScienceGate Book Chapters

JOURNAL ARTICLE

<title>Image restoration by multiscale entropy</title>

Jean‐Luc Starck

Year: 1999 Journal: Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 3813 Pages: 97-107 Publisher: SPIE

DOI: 10.1117/12.366843

Get Full-Text PDF Get Analytical Report

Abstract

We present in this paper a new way to measure the information in a signal, based on noise modeling. We show that the use of such an entropy-related measure leads to good results for signal restoration.

Keywords:

Image restoration Entropy (arrow of time) Measure (data warehouse) Computer science Artificial intelligence SIGNAL (programming language) Speech recognition Image (mathematics) Data mining Image processing Physics

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.14

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

Image and Signal Denoising Methods

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Image Processing Techniques and Applications

Physical Sciences → Engineering → Media Technology

<title>Image restoration by multiscale entropy</title>

Abstract

Metrics

Topics

Related Documents

<title>Closed-form maximum entropy image restoration</title>

<title>Multiscale image restoration for photon imaging systems</title>

<title>Multiscale image coder</title>

<title>Genetic algorithm for maximum entropy image restoration</title>

<title>Image-restoration aggregation</title>