الفهرس 
Discovery of the Infrared Radiation
Image Quality MetricsOnly 14 pages are availabe for public view
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Abstract
This thesis is concerned with the enhancement of the infrared (IR) night vision images as the IR images have low visual quality. There are several applications for IR imaging such as medical and military applications including target acquisition, surveillance, night vision, and tracking. The aim of image enhancement is improving the visibility of IR images and reducing the noise to obtain an image with as much details as possible. This thesis presents three proposed approaches for enhancing the visibility of IR night vision images. The first one depends on gamma correction. This approach is based on merging gamma correction with Histogram Matching (HM). The second one depends gamma correction and Contrast-Limited Adaptive Histogram Equalization (CLAHE). The HM needs a reference visual image for converting the IR night vision images into images with better visual quality.
Finally, the third proposed approach is based on trilateral contrast enhancement, where IR night vision images pass through three stages: segmentation, enhancement and sharpness. In the first stage, IR images are divided into groups of segments. The second stage is the most important process in the enhancement that depends on Additive Wavelet Transform (AWT) with Homomorphic enhancement (AWTH). The benefits of the AWT are first exploited. The image is decomposed into sub-bands using the AWT. Then, each sub-band is processed, separately, using the homomorphic approach to reinforce its details. The third stage is a sharpness stage in which a boosting filter is applied to the resultant IR image to sharpen edges for better visual quality. To measure the performance of the proposed techniques, evaluation metrics such as entropy , average gradient, Sobel edge magnitude and spectral entropy are used.