Advanced Image Haze Removal Using Denoising and Dehazing Algorithm with Compression

1 PG Scholar , Paavai Engineering College, Namakkal, 2 M .E., Associate professor ,Department of ECE, Paavai engineering college,Namakkal Received 25 November 2015; Accepted 4 December 2015 ABSTRACT: Single image haze removal has been a demanding problem due to its ill-posed nature. Images captured in hazy weather environment often suffer from poor illumination conditions that will create a lot of impact on the outer Computer vision systems, such as video surveillance, intelligent traffic assistance system, remote sensing and space cameras soon. In proposed system, two methods for removing both haze and noise from a single image is used. The first approach is to de noise the image prior to de hazing. This serial approach essentially treats haze and noise separately, and so a second approach is proposed to simultaneously de noise and de haze using an iterative, adaptive, nonparametric regression method. Our findings show that when the noise level is precisely known a priori, simply de noising prior to de hazing performs well. When the noise level is not given, underlying errors from either low level denoising or high noising can be a intensified, and in this situation, the repetitious approach can yield superior results.