Haze is an atmospheric phenomenon that degrades the clarity of an image by scattering the light between the scene and the image acquisition system due to dust, smoke, and other particles. The current project presents a haze removal method, based on a linear model, which is used for estimating the scene depth. Results from real images under different haze conditions are presented. Images dehazed with the proposed method are compared to images dehazed with the Dark Channel Prior (DCP) method. Analysis of the Peak Signal to Noise Ratio (PSNR) values shows that while the DCP method tends to degrade rapidly as haze levels increase, the proposed method provides consistently superior PSNR characteristics even for high levels of haze.
|Commitee:||Khoo, I-Hung, Yeh, Hen-Guel|
|School:||California State University, Long Beach|
|School Location:||United States -- California|
|Source:||MAI 56/03M(E), Masters Abstracts International|
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