A Comparative Study of Noise Removal in Remote Sensing Images

International Journal of Computer Science (IJCS Journal) Published by SK Research Group of Companies (SKRGC) Scholarly Peer Reviewed Research Journals

Format: Volume 1, Issue 2, No 4, 2013.

Copyright: All Rights Reserved ©2013

Year of Publication: 2013



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Noise reduction is a prerequisite step prior to many information extraction attempts from remote sensing images. Reducing noise in remote sensing image restoration problem in that it endeavour to recover on original perfect image from a corrupted copy. This problem is intractable unless one makes assumptions about actual structure of the perfect image. Various noise filters make various assumptions depending on the type of image and the goals of the restoration. This paper presents kalman filter for gray scale images contaminated by noise. Remote sensing images are affected by different types of noise like Gaussian noise, Speckle noise and impulse noise. These noises are introduced into the Remote Sensing image during acquisition or transmission process. In this paper wiener filter and kalman filter is used for reduce the noise rate, when compare to this filters, kalman gives better results.


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Remote sensing image, wiener filter, kalman filter, gaussion noise.

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