Investigation of Fuzzy and SOM based Segmentation of High-Resolution Satellite Images in HSL Color Space for Information Retrieval

In the proposed article, an innovative approach for the segmentation of region of interest (ROI) based on fuzzy and neural network (SOM-self organizing map) is investigated. In image analysis, clustering is an unique imperative practice wherein the complete data is separated as group of pixels and/or regions using its features. A satellite image is huge collection information. Many approaches and algorithms suggested for the dissection of satellite imagesto extract the indispensable and hidden information. In this work, fuzzy based FCM, PCM, PFCM, MFCM and SOM is applied to the satellite images to retrieve the information. The proposed method transforms the image in RG to HSL model prior to clustering. HSL model has some distinct characteristics such as perceptual, intuitive, polar coordinated, approximate the vision. The segmentation result is validated with image quality measures.