tailieunhanh - Satellite image enhancement and restoration – A review

This review paper presents various techniques applied in satellite image enhancement and restoration. Our review findings shows that there exists lot of scope for performing satellite image enhancement and restoration using amalgamating soft computing techniques and conventional image processing. | ISSN:2249-5789 S Maheshwari et al, International Journal of Computer Science & Communication Networks,Vol 6(4),198-204 Satellite Image Enhancement and Restoration – A Review 1 , 1 Assistant Professor, PG & Research Department of Computer Science Arts and Science College, Coimbatore-48 sivamahesh@ 2 Director - Department of Computer Applications, CIMAT, Coimbatore, India, pkpriyaa@ Abstract Satellite image processing is one of the thrust areas in the field of computer science research. Images taken by satellites possibly degraded due to climate, weather and other factors. Satellite image enhancement and restoration is scientifically possible by applying image processing and other soft computing techniques. This review paper presents various techniques applied in satellite image enhancement and restoration. Our review findings shows that there exists lot of scope for performing satellite image enhancement and restoration using amalgamating soft computing techniques and conventional image processing. The proposed doctoral research work is descriptively portrayed in the paper. Keywords: Satellite imagery, satellite image processing, enhancement, restoration, fusion. 1. Introduction The purpose of image enhancement and restoration techniques is to perk up a quality and feature of a satellite image that result in improved image than the original one. There exist so many image enhancement algorithms in the literatures that most often IJCSCN | August-September 2016 Available online@ used techniques as global histogram equalization or general histogram equalization [1]. Usually histogram equalization technique alters the intensity histogram in order to fairly accurate a uniform distribution. The major pitfall of this histogram equalization technique is the problem of covering global image properties that may not be appropriately applied in a local context [2]. It is noteworthy that histogram .