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.
 Ranganath R., Navalgund, V. Jayaraman and P. S. Roy “Remote sensing applications: An overview” Special Section: Indian Space of technology. Mr. Salem Saleh Al-amir, Dr. N.V. Kalyankar and Dr. S. D. Khamitkar, “A Comparitive Study of Removal Noise from Remote Sensing Image”, IJCSI, Vol. 7, Issue. 1,No.1, January 2010 S. K. Satpathy, S. Panda, K. K. Nagwanshi, S.K. Nayak and c. Ardil, “Adaptive Non-Linear Filtering Technique for Image Restoration”, IJECE 5:1 2010. Mrs. V. Radhika and Dr. G. Padmavathi, “Performance of Various Order Statistics Filters in Impulse and Mixed Noise Removal for RS Images”, SIPIJ, Vol,1, No.2, December 2010.Rafael C. Gonzalez, Richard Eugene Woods, Steven L. Eddins , “Digital Image processing”, 2004 Masayoshi Tsuchida,* Miki Haseyama, and Hideo Kitajima, “A Kalman Filter Using Texture for Noise Reduction in SAR Images”, Electronics and Communications in Japan, Part 1, Vol. 86, No. 10, 2003 Dan Simon, “Kalman Filtering”, Embedded Systems Programming, June, 2001. M. Prema Kumar, P.H.S.Tejo Murthy and Dr.P.Rajesh Kumar, “Performance Evaluation of Different Image Filtering Algorithms Using Image Quality Assessment”, IJCA, Vol. 18, No.6, March 2011. J. Astola and P. Kuosmanen, Fundamentals of Nonlinear Digital Filtering, Boca Raton, FL: CRC, 1997. Andrew A. Green, Mark Berman, Paul Switzer and Maurice D. Graig, “A Transform for Ordering Multispectral Data in terms of Image Quality with Implications for noise removal”, IEEE, Vol. 26, No.1 January 1988Jaako Astola, and Yrjo Neuvo, “Optimal Weighted Median Filtering Under Structural Constrains”,IEEE, Vol, 43, No,3, March 1995. Eong-Seok Yu, Joon-Yeop Lee and Jun-Dong Senior Member, “A Fast Sorting Algorithm for General Purpose Standard Median Filters in VLSI implementation”, IEEE Behrooz Ghandeharian, Hadi Sadoghi Yazdi and Faranak Homayouni, “Modified Adaptive Centre Eighted Median Filt er for Uppressing Impulsive Noise in Images”, IJRRAS, Vol,1, Issue.3, December 2009.
Remote sensing image, wiener filter, kalman filter, gaussion noise.