An Unsharp Masking Algorithm Embedded With Bilateral Filter System for Enhancement of Aerial Photographs

Human visual system is more sensitive to edges and ridges in the images which composed of high spatial frequency components. Digital images having more spatial variations may contain informative content than their counterparts. Remote sensing images are one of those categories covering different aspects of land surface variations, aerial photographs are obtained on board image sensors on flying platform. Aerial photographs represent the land surfaces consists of textural and structural objects make more presence of edges. Interpolating information of aerial photographs become clumsy when the pixels are corrupted with noises at different density of levels. The kind of aerialphotographsare acquired in various way such as multi/hyper spectral sensors on board of satellites or the planes, by synthetic aperture radar (SAR) in remote sensing. The intelligence of the aerial photographs affected because of noises during image formation process and atmospheric factors. In this paper, unsharp masking (USM) algorithm based image denoising framework is proposed with Gaussian and bilateral filters. Structure similarity index(SSIM) and Image enhancement factor (IEF) based performance comparisons were studied for various noises on aerial photographs and the experimental results shown that the bilateral filter with USM system outperforms the Gaussian filter with USM. The simulation setup demonstrated using both additive and multiplicative noises with the different levels of noise density on aerial photographs.