This paper is published in Volume-5, Issue-3, 2019
Area
Electronics and Telecommunication
Author
Devray Renuka Nitin, Atul Shreevastav
Org/Univ
Vishwabharati Academy's College of Engineering, Ahmednagar, Maharashtra, India
Keywords
Underwater, Image fusion, White balancing
Citations
IEEE
Devray Renuka Nitin, Atul Shreevastav. Review on underwater image enhancement using multiscale fusion, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Devray Renuka Nitin, Atul Shreevastav (2019). Review on underwater image enhancement using multiscale fusion. International Journal of Advance Research, Ideas and Innovations in Technology, 5(3) www.IJARIIT.com.
MLA
Devray Renuka Nitin, Atul Shreevastav. "Review on underwater image enhancement using multiscale fusion." International Journal of Advance Research, Ideas and Innovations in Technology 5.3 (2019). www.IJARIIT.com.
Devray Renuka Nitin, Atul Shreevastav. Review on underwater image enhancement using multiscale fusion, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Devray Renuka Nitin, Atul Shreevastav (2019). Review on underwater image enhancement using multiscale fusion. International Journal of Advance Research, Ideas and Innovations in Technology, 5(3) www.IJARIIT.com.
MLA
Devray Renuka Nitin, Atul Shreevastav. "Review on underwater image enhancement using multiscale fusion." International Journal of Advance Research, Ideas and Innovations in Technology 5.3 (2019). www.IJARIIT.com.
Abstract
We introduce an effective technique to enhance the images captured underwater and degraded due to the medium scattering and absorption. Our method is a single image approach that does not require specialized hardware or knowledge about the underwater conditions or the scene structure. It builds on the blending of two images that are directly derived from a color compensated and white balanced version of the original degraded image. The two images to fusion, as well as their associated weight maps, are defined to promote the transfer of edges and color contrast to the output image. To avoid that the sharp weight map transitions create artifacts in the low-frequency components of the reconstructed image, we also adopt a multiscale fusion strategy. Our extensive qualitative and quantitative evaluation reveals that our enhanced images and videos are characterized by better exposedness of the dark regions, improved global contrast, and edges sharpness. Our validation also proves that our algorithm is reasonably independent of the camera settings, and improves the accuracy of several image processing applications, such as image segmentation and keypoint matching.