Most outdoor visual systems such as video surveillance, target tracking, remote sensing and navigation control and vehicle autonomous driving and others are highly vulnerable to harsh environment, especially because of fog and haze. Images of outdoor scene can be significantly degraded due to the bad weather condition such as fog and haze. Thus it lead to the atmospheric scattering of tiny water droplets and atmospheric aerosol on the scene point, causing image fuzzy, bad visibility, and seriously affecting the performance of an outdoor system. This happens because of the presence of numerous atmospheric particles which absorbs and scatters light. Such degraded images lose all its contrast and become dim especially in the distant regions and get blurred with their surroundings area. In order to make the system robust and reliable in bad weather conditions, it is necessary to dehaze that degraded image.
This paper focus on the digital hazy image restoration. Here image store the edge region of the image then apply Laplace distribution for pixel value restoration. Here whole work is explained in fig.
Here as the image is the collection of pixels where each pixel is representing a number that is reflecting a number over there now for each number depend on the format it has its range. So read a image means making a matrix of the same dimension of the image then fill the matrix correspond to the pixel value of the image at the cell in the matrix.
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