Title :
Compression ratio prediction in lossy compression of noisy images
Author :
Alexander N. Zemliachenko;Sergey Abramov;Vladimir V. Lukin;Benoît Vozel;Kacem Chehdi
Author_Institution :
National Aerospace University, 61070, Kharkov, Ukraine
fDate :
7/1/2015 12:00:00 AM
Abstract :
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 offline (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.
Keywords :
"Image coding","Discrete cosine transforms","Noise measurement","Standards","Hyperspectral imaging","Fitting"
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
Electronic_ISBN :
2153-7003
DOI :
10.1109/IGARSS.2015.7326574