DocumentCode :
640791
Title :
Efficiency of lossy compression of noisy and pre-filtered remote sensing images
Author :
Lukin, V.V. ; Zemliachenko, A.N. ; Tchobanou, M.K.
Author_Institution :
Dept. of Signal Transm., Nat. Aerosp. Univ., Kharkov, Ukraine
fYear :
2013
fDate :
23-28 June 2013
Firstpage :
343
Lastpage :
345
Abstract :
This paper state that pre-filtering of noisy image before compression can provide certain benefits only under several conditions. First, a noisy image to be compressed has to have a rather simple structure. Second, noise intensity is to be rather high; only in this case pre-filtering is able to produce considerable improvement of visual quality compared to noisy image. In the case when a pre-filtered image is subject to compression, benefits due to pre-filtering are observed only if compression ratio (quantization step) is not too large. Moreover, we have not observed OOP for pre-filtered and then compressed images. Thus, their quality (according to both standard and HVS-metrics) permanently decrease if compression ratio increases. If CR has to be large, there is no reason to perform pre-filtering of noisy images.
Keywords :
data compression; filtering theory; geophysical image processing; image coding; quantisation (signal); remote sensing; HVS-metric; lossy compression; noise intensity; noisy remote sensing images; prefiltered remote sensing images; quantization step; standard metric; visual quality improvement; Hyperspectral sensors; Image coding; Noise; Noise measurement; Standards; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves (MSMW), 2013 International Kharkov Symposium on
Conference_Location :
Kharkiv
Print_ISBN :
978-1-4799-1066-3
Type :
conf
DOI :
10.1109/MSMW.2013.6622050
Filename :
6622050
Link To Document :
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