Survey on Hyperspectral Image Denoising

 In image processing noisy images cause harmful effect on subsequent application and degrade visual quality of their particular views. The term denoising refers to method of estimating the unknown (original) signal from available noisy data. Hyperspectral imaging has been proved that it has many applications in agriculture, diagnostic medicine, and military surveillance. However, in these applications, the presence of the noise decreases significantly the classification accuracy by blurring the boundaries of objects of interest and affects the accurate determination of irregularly occurring end members. HSI denoising is very important preprocessing step before these images/data are analyzed. This paper is analyzing some techniques of hyperspectral image denoising and shows their performance in reducing noise. This paper describes various approaches to achieve better hyperspectral image denoising in some depth.