COMPRESSION RATIO PREDICTION IN LOSSY COMPRESSION OF NOISY IMAGES

被引：0
|
作者：
Zemliachenko, Alexander N. [1 ]
Abramov, Sergey [1 ]
Lukin, Vladimir V. [1 ]
Vozel, Benoit [2 ]
Chehdi, Kacem [2 ]
机构：
[1] Natl Aerosp Univ, UA-61070 Kharkov, Ukraine
[2] Univ Rennes 1, CNRS, UMR 6164, ILTR, F-22305 Lannion, France
来源：
2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2015年
关键词：
remote sensing; lossy compression; noise; hyperspectral; prediction;
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：
Our paper addresses a question of prediction compression ratio in lossy compression of remote sensing images by coders based on discrete cosine transform (DCT) taking into account noise present in these images. Quantization step is set fixed and proportional to noise standard deviation to provide compression in optimal operation point if it exists. Simple statistics of DCT coefficients is used for predicting compression ratio. Prediction dependences are obtained off-line (in advance) and they occur to be quite simple and accurate. The influence of DCT statistics on prediction efficiency is analyzed. Accuracy of prediction is studied for real-life hyperspectral data compressed component-wise.
引用
收藏
页码：3497 / 3500
页数：4
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