Modified Double Bilateral Filter for Sharpness Enhancement and Noise
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Adaptive Bilateral filters are well known for removing the gaussian noise from images. Bilateral filtering smooth images while preserving edges, by means of a nonlinear combination of nearby image values. The method is noniterative, local, and simple. It combines gray levels or colors based on both their geometric closeness and their photometric similarity, and prefers near values to distant values in both domain and range. In this book, a new sharpening and smoothing algorithm: the Modified Adaptive Bilateral filter (MABF) is proposed. The proposed method, unlike other nonlinear filters, remo...
Adaptive Bilateral filters are well known for removing the gaussian noise from images. Bilateral filtering smooth images while preserving edges, by means of a nonlinear combination of nearby image values. The method is noniterative, local, and simple. It combines gray levels or colors based on both their geometric closeness and their photometric similarity, and prefers near values to distant values in both domain and range. In this book, a new sharpening and smoothing algorithm: the Modified Adaptive Bilateral filter (MABF) is proposed. The proposed method, unlike other nonlinear filters, removes only corrupted pixel by the median value or by its neighboring pixel value. As a result it removes the noise effectively even at noise level as high as 90% and preserves the edges without any loss up to 80% of noise level. The new proposed Modified Adaptive Bilateral Filter is efficient for restoration of images which are highly corrupted by combined gaussian and impulse noise.
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