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RESEARCH PRODUCT

High Order Textural Classification of Two SAR ERS Images on Mount Cameroon

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Abstract Many researchers have demonstrated that textural data increase the precision of a classification when they are combined with level of grey information. However, the calculation of textural parameters of order two is often too long in a computer. The problem is more complex when one must compute higher order textural parameters, which however can considerably improve the precision of a classification. This work is based on statistical methods of order two and three for the calculation of textural parameters [Akono et al., 2003]. In this work, we suggest a new method of calculation of textural parameters, which is more general, not limiting itself only on order two or three, but which goes until an order n > 2, but still remaining applicable to orders two and three. The principle of this study consists in reducing the calculation of a n‐summation of type ( ) generally utilized in the evaluation of textural parameters, to a simple summation of type . ψ is a function depending on the matrix frequency...