Published 12 issues per year
ISSN Print: 0040-2508
ISSN Online: 1943-6009
Indexed in
Joint Estimation of Remote Sensing Images and Mixed Noise Parameters
ABSTRACT
We address a joint task of remote sensing image enhancement and noise parameters’ estimation within a maximum likelihood framework. Estimation (blind determination) of noise parameters is an important operation in pre-processing images formed in varying or unknown imaging conditions. One peculiarity of our approach is that fractals (fBm-model) are used for modeling real-life images. Another peculiarity and advantage of the proposed approach consists in simultaneous evaluation of additive correlated noise variance and impulse noise occurrence probability. The core of our method is an iterative procedure of impulse noise detection and estimation of additive noise variance using pixels that are considered uncorrupted by impulses. Image model parameters are estimated as well with providing additional information for image interpretation. The designed method is tested for simulated and real life remote sensing images.
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Lukin Vladimir V., Methods and automatic procedures for processing images based on blind evaluation of noise type and characteristics, Journal of Applied Remote Sensing, 5, 1, 2011. Crossref
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Uss Mikhail, Vozel Benoit, Chehdi Kacem., Lukin V. V., Abramo S. K., The minimum number of scanning windows required for effective maximum likelihood estimation of image texture parameters and additive noise variance, 2010 INTERNATIONAL KHARKOV SYMPOSIUM ON PHYSICS AND ENGINEERING OF MICROWAVES, MILLIMETER AND SUBMILLIMETER WAVES, 2010. Crossref