EFFECT OF DEGRADATION ON MULTISPECTRAL SATELLITE IMAGE

Satellite images record electromagnetic radiation intensity that emitted or reflected from Earth's object within the field of view (FOV) of satellites sensor. These radiations are affected by the turbulent atmosphere and other effects (like noise and motion detectors), thus will reduce the quality of acquired images. The degree of distortion depends on wavelength, and since satellite images are taken in different wavelengths (multispectral bands) including visible and infrared (emitted and reflected). So, each band of satellite images will have different value of distortion. In this work, computer program (using matlab language) has been written to study the degradation effect parameters for each band of Landsat7 satellite image. The main objective is to show which band has less effect. It is found that band3 (0.630-0.690 m ), band4 (0.750-0.900 m ) and band7 (3.090-2.350 m ) has great atmospheric effect for vegetation, water and sand area respectively. Archive of these areas is build up to estimated parameters used for recovery other images. Result shows that when the size of the recovered area is small best results are obtained from it. Introduction Satellite images are often recorded under a wide variety of circumstance. As imaging technology is rapidly advancing. Since our technology is not perfect, every recorded satellite image is a degraded version of the scene in some sense. Every imaging system has a limit to its available resolution and the speed at which images can be recorded. Some unusual sensory abilities are present in natural world, such as the ability to detect magnetic and electric fields, or the use of ultrasound waves to determine the structure of surrounding obstacles [1]. The current understanding about the nature of light and color can be traced to the work of the Sir Isaac Newton. The light is characterized physically by its spectral composition [2]. Multispectral imaging entails acquiring several images of the same scene using different spectral bands [3]. Collecting several spectral bands generally provides more information than would be obtained from a single monochrome image. This idea has been applied in the field of remote sensing for over 20 years. Landsat Earth observation satellites are capable of acquiring multispectral bands spanning visible and non-visible wavelengths such as infra-red. The full set can be processed to identify different kinds of land use automatically [3]. The former type of data collection can be accomplished by different sensors operating simultaneously (multisensor) or by a single sensor that operates in several spectral regions simultaneously (multispectral or multiband sensor) [4]. Theory The degradation process model consists of two parts, the blurring function and the noise function. The general formation model in the spatial domain is given by [5]: ) y , x ( n ) y , x ( f ) y , x ( h ) y , x ( g ...(1) Where denotes the convolution process g(x,y)=degraded image. h(x,y)= blurring function. f(x,y)=original image n(x,y)=additive noise function Because convolution in the spatial domain is equivalent to multiplication in the frequency domain, the frequency model is [5]: