6533b824fe1ef96bd1280902

RESEARCH PRODUCT

A Parallel Approach for Statistical Texture Parameter Calculation

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This chapter focusses on the development of a new image processing technique for the processing of large and complex images, especially SAR images. We propose here a new and effective approach that outperforms the existing methods for the calculation of high order textural parameters. With a single processor, this approach is about \(256^{n-1}\) times faster than the co-occurrence matrix approach considered as classical, where \(n\) is the order of the textural parameter for a 256-gray scales image. In a parallel environment made of N processor, this performance can almost be multiply by the factor N. Our approach is based on a new modeling of textural parameters of a generic order \(n>1\) equivalent to the classical formulation, but which is no longer based on the co-occurrence matrix of order \(n>1\). By avoiding the calculation of the co-occurrence matrix of order \(n>1\), the resulted model enables a gain of about \(256^{n}\) bytes of the required memory space.