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https://www.ias.ac.in/article/fulltext/jess/118/05/0609-0617

High resolution image; texture analysis; segmentation; IKONOS; Hölder exponent; cluster.

Texture in high-resolution satellite images requires substantial amendment in the conventional segmentation algorithms. A measure is proposed to compute the Hölder exponent (HE) to assess the roughness or smoothness around each pixel of the image. The localized singularity information is incorporated in computing the HE. An optimum window size is evaluated so that HE reacts to localized singularity. A two-step iterative procedure for clustering the transformed HE image is adapted to identify the range of HE, densely occupied in the kernel and to partition Hölder exponents into a cluster that matches with the range. Hölder exponent values (noise or not associated with the other cluster) are clubbed to a nearest possible cluster using the local maximum likelihood analysis.

Debasish Chakraborty¹ Gautam Kumar Sen² Sugata Hazra²

1. Regional Remote Sensing Service Centre, Indian Space Research Organization, IIT Campus, Kharagpur 721 302, India.
2. School of Oceanographic Studies, Jadavpur University, Kolkata 700 032, India.

Published

October 2009

Manuscript received

4 July 2008

Manuscript revised

2 June 2009

Accepted

6 June 2009