High-resolution satellite image segmentation using Hölder exponents

Autor:	Debasish Chakraborty, Sugata Hazra, Gautam Kumar Sen
Rok vydání:	2009
Předmět:	Singularity Smoothness (probability theory) Pixel Kernel (image processing) General Earth and Planetary Sciences Segmentation Noise (video) Cluster analysis Algorithm Measure (mathematics) Mathematics Remote sensing
Zdroj:	Journal of Earth System Science. 118:609-617
ISSN:	0973-774X 0253-4126
Popis:	Texture in high-resolution satellite images requires substantial amendment in the conventional seg- mentation algorithms. A measure is proposed to compute the Holder 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 Holder expo- nents into a cluster that matches with the range. Holder exponent values (noise or not associated with the other cluster) are clubbed to a nearest possible cluster using the local maximum likelihood analysis.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::20504dbe956677d16268cc4479400297 https://doi.org/10.1007/s12040-009-0044-3 Zobrazit plný text záznamu Full text from SpringerLink