Prediction of DCT-based Denoising Efficiency for Images Corrupted by Signal-Dependent Noise

被引：0

作者：

Krivenko, Sergey ^{[1
]}

Lukin, Vladimir ^{[1
]}

Vozel, Benoit ^{[2
]}

Chehdi, Kacem ^{[2
]}

机构：

[1] Natl Aerosp Univ, Dept Transmitters Receivers & Signal Proc, Kharkov, Ukraine

[2] Univ Rennes 1, IETR, CNRS, UMR 6164, Lannion, France

来源：

2014 IEEE 34TH INTERNATIONAL CONFERENCE ON ELECTRONICS AND NANOTECHNOLOGY (ELNANO) | 2014年

关键词：

image denoising; efficiency prediction; DCT; signal-dependent noise;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper describes a simple and fast way to predict efficiency of DCT-based filtering of images corrupted by signal dependent noise as this often happens for hyperspectral and radar remote sensing. Such prediction allows deciding in automatic way is it worth applying denoising to a given image under condition that parameters of signal-dependent noise are known a priori or pre-estimated with appropriate accuracy. It is shown that denoising efficiency can be predicted not only in terms of traditional quality criteria as output MSE or PSNR but also, with slightly less accuracy, in terms of visual quality metrics and PSNR-HVS-M.

引用

页码：254 / 258

页数：5

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