Title :
Self-organizing feature map based polarimetric SAR data denoising
Author :
Shitole, Sanjay ; Rao, Y.S. ; Mohan, B. Krishna ; Das, Aruneema
Author_Institution :
Centre of Studies in Resources Eng., Indian Inst. of Technol. Bombay, Mumbai, India
Abstract :
Speckle has a nature of multiplicative noise which is difficult to deal as compared to additive noise. It complicates the problem of interpretation of the image segmentation and classification. The primary goal of existing speckle filtering algorithms, which are subjective in nature is to reduce the speckle without loss of information. Various techniques have been proposed to suppress the speckle. In this paper we propose Self-Organizing Feature Map (SOFM) based polarimetric SAR speckle filter. The filter is evaluated using fully polarimetric ALOSPALSAR and Radarsat-2 data imaged over Mumbai, India. Quantitative and qualitative results revels that SOFM based approach is effective in terms of bias and speckle reduction.
Keywords :
filtering theory; geophysical image processing; geophysical techniques; image classification; image denoising; image segmentation; radar polarimetry; remote sensing by radar; self-organising feature maps; speckle; synthetic aperture radar; India; Mumbai; Radarsat-2 data; SOFM based polarimetric SAR speckle filter; additive noise; fully polarimetric ALOSPALSAR data; image classification; image segmentation; multiplicative noise; polarimetric SAR data denoising; self-organizing feature map; speckle filtering algorithm; speckle reduction; speckle suppression; Arrays; Image segmentation; Indexes; Speckle; Synthetic aperture radar; Training; Vectors; IDAN filter; Improved Sigma filter; Polarimetric SAR; Self-Organizing Feature Map; Speckle Filter;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4799-1114-1
DOI :
10.1109/IGARSS.2013.6723296