Wavelet multiscale processing of remote sensing data

Valeriy H. Bagmanov; Svyatoslav V. Kharitonov; Ivan K. Meshkov; Albert H. Sultanov

doi:10.1117/12.829035

3 April 2009 Wavelet multiscale processing of remote sensing data

Valeriy H. Bagmanov, Svyatoslav V. Kharitonov, Ivan K. Meshkov, Albert H. Sultanov

Proceedings Volume 7374, Optical Technologies for Telecommunications 2008; 73740G (2009) https://doi.org/10.1117/12.829035
Event: Optical Technologies for Telecommunications 2008, 2008, Kazan, Russian Federation

Abstract

There is comparative analysis of methods for estimation and definition of Hoerst index (index of self-similarity) and comparative analysis of wavelet types using for image decomposition are offered. Five types of compared wavelets are used for analysis: Haar wavelets, Daubechies wavelets, Discrete Meyer wavelets, symplets and coiflets. Best quality of restored image Meyer and Haar wavelets demonstrate, because of they are characterised by minimal errors of recomposition. But compression index for these types smaller, than for Daubechies wavelets, symplets and coiflets. Contrariwise the latter obtain less precision of decompression. As it is necessary to take into consideration the complexity of realization some wavelet transformation on digital signal processors (DSP), simplest method is Haar wavelet transformation.

Citation Download Citation

Valeriy H. Bagmanov, Svyatoslav V. Kharitonov, Ivan K. Meshkov, and Albert H. Sultanov "Wavelet multiscale processing of remote sensing data", Proc. SPIE 7374, Optical Technologies for Telecommunications 2008, 73740G (3 April 2009); https://doi.org/10.1117/12.829035

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