Noise Removal in Remote Sensing Image Using Kalman Filter Algorithm

Abstract: Noise reduction is a prerequisite step prior to information extraction that attempts from remote sensing images. Reducing Noise in remote sensing Image is an image restoration problem to recover a original image from the corrupted Images. This problem is intractable unless one can make assumptions about the actual structure of the perfect image. Various Noise removing filters make various assumptions depending on the type of image and the goals of the restoration. In this paper Kalman filter is used for gray scale images which is 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 in the Remote Sensing image during acquisition or transmission process. In this paper wiener filter and kalman filter is used for reducing the Noise rate, when compare to some other filters. In this the Proposed kalman filter gives better results when compared to Wiener filter.

Keywords: Remote Sensing Image, Wiener filter, Kalman filter, Gaussian Noise.