الفهرس 
Chapter 1 IntroductionOnly 14 pages are availabe for public view
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Abstract
The thesis is concerned with infrared (IR) image processing. There are
several applications for IR imaging such as medical and military applications
including target acquisition, surveillance, night vision, homing and tracking. IR
imaging techniques can be used to image the temperature distribution of an
object. In medical applications, IR imaging is helpful in the diagnosis and
prediction of several diseases.
IR images have low contrast between background and targets and small
Signal-to-Noise Ratios (SNRs). These characteristics reduce the detectability of
targets from IR images. In order to recognize targets correctly from these images
good enhancement approaches must be applied apriori. The aim of image
enhancement is to improve the visibility of low-contrast images and decreasing
the noise to obtain an image with as much details as possible.
In this thesis, two suggested enhancement approaches for IR images are
presented; a visual quality enhancement approach and a resolution enhancement
approach. The visual quality approach is based on the Additive Wavelet
Transform (AWT) and the homomorphic transform. The resolution enhancement
approach is based on image interpolation. A Least-Squares (LS) image
interpolation approach with its mathematical model is presented in this thesis.
This approach treats the image interpolation problem as an inverse problem
taking into consideration the Low-Resolution (LR) image degradation model to
obtain High-Resolution (HR) images.