Abstract
In this paper, a highly adaptive swarm intelligence optimized dark image enhancement approach is proposed for remotely sensed satellite images. Here, a weighted summation framework is suggested for imparting “on-demand entropy restoration and contrast enhancement”. This approach utilizes the benefits of both gamma correction and histogram equalization; and hence, overall image enhancement can be appropriately imposed without losing original image features, especially for dark satellite images. For further improvement, gamma correction is also employed in a piecewise manner, separately for dark as well as light pixel values, so that over-saturation and other related unnatural artifacts can be avoided. A suitable entropy and contrast based cost function is utilized, and its maximization is done by employing particle swarm optimization over a three-dimensional search space. The proposed approach is found to be highly appreciable for overall enhancement, preserving all the intrinsic visual details for a wide range of dark image database covering satellite as well as general images.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
