PROJECT TITLE :

Efficient naturalistic approach to image contrast enhancement

ABSTRACT:

Distinction enhancement is a crucial step in many image processing and analysis applications. Although the idea of enhancing image contrast is easy, most printed mechanisms of letting computers do therefore automatically have a tendency to be complex or not therefore intuitive, and the performance is generally not consistent across completely different image shooting conditions. A new naturalistic approach to the present downside that directly mimics what an individual's artist would do for contrast enhancement is proposed. The goal is to create each non-noise detail easily perceivable by a traditional human. Specifically, the gradient/distinction and native background are computed for each pixel and then linearly mapped to an objective purpose in the gradient-background plane. Then, a cross-bilateral filter is employed to swish the two linear map parameter images. A moving local window is used to obtain the native noise level for each pixel, that is used to see whether the pixel should be enhanced. The proposed approach is straightforward to implement and results in superior results compared with typical state-of-the-art strategies, as confirmed by experimental results.


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