Image Fusion in SAR Images Using Fuzzy Clustering

EasyChair Preprint no. 9894

Abstract

This study provides a unique fuzzy clustering algorithm and an image fusion

technique for an unsupervised distribution-free change detection method for synthetic

aperture radar (SAR) images. the introduction of the picture fusion technique to

produce a difference image by combining data from an image with a mean ratio and an

image with a log ratio. The wavelet coefficients for a low-frequency band and a high-

frequency band are fused, respectively, using wavelet fusion rules based on an average

operator and minimum local area energy in order to limit background information and

enhance the information of changed regions in the fused difference image. For

categorizing modified and unaffected regions in the fused difference image, a

reformulated fuzzy local-information C-means clustering technique is suggested. It

includes details on the spatial context.

Keyphrases: Clustering, fuzzy c-means (FCM) algorithm, image change detection, image fusion, Synthetic Aperture Radar (SAR)

@Booklet{EasyChair:9894,
  author = {Atul Kumar Yadav and Shubhankar Vishwakarma},
  title = {Image Fusion in SAR Images Using Fuzzy Clustering},
  howpublished = {EasyChair Preprint no. 9894},

  year = {EasyChair, 2023}}