الفهرس 
الغلافOnly 14 pages are availabe for public view
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Abstract
Remote sensing can be broadly defined as the collection and interpretation of inforn1.ation about an object, area, or event without being in physical contact with the object.
Remote sensing image processing is nowadays a mature research area in many applications urban monitoring, fire detection, flood prediction, etc. Remote sensing has turned into a multidisciplinary field of sciences; signal theory, computer science, electronics, and communication. Image processing requires techniques such as classification and clustering, image coding, restoration and enhancement, data fusion or feature selection and extraction. Image restoration and enhancement module is a vital part as a preprocessing for any image processing technique.
This thesis provides a survey of various spatial and transforms de-noising techniques for different types of remote sensing images contaminated with different types of noises. The thesis reviews the last methodological advances in de-noising remote sensing image.
This thesis proposes an adaptive threshold technique based on wavelet transform to reduce noise of gray scale of remotely sensed images from speckle noise and gaussian noise then compare the results of proposed technique with different techniques based on wavelet transfonn as Universal