Mitigating the Blurriness of Underwater Images and Quality Enhancement
P. Ajanya1, R. Balakrishna2, A. Sajeev Ram3
1P.Ajanya, Student, Department of Computer Science and Engineering, Vels Institute of Science Technology & Advanced Studies VISTAS, Chennai (Tamil Nadu), India.
2R.Balakrishna, Assistant Professor, Department of Computer Science and Engineering, Vels Institute of Science Technology & Advanced Studies VISTAS, Chennai (Tamil Nadu), India.
3A.Sajeev Ram, Assistant Professor, Department of Computer Science and Engineering, Vels Institute of Science Technology & Advanced Studies VISTAS, Chennai (Tamil Nadu), India.
Manuscript received on 25 May 2019 | Revised Manuscript received on 03 June 2019 | Manuscript Published on 22 June 2019 | PP: 11-14 | Volume-8 Issue-3S, February 2019 | Retrieval Number: C10030283S19/19©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Capturing an apparent picture from the bottom of the water bodies had been an important concern and challenge from the past. While alleviating the artifacts of underwater pictures, some contrast enhancement can be missing due to sharpening artifacts. Because of Multi scale fusion’s complexity and much execution time, we proposed color attenuation prior model based on depth & scattering restoration, color balance and modified white balance technique and Multi-scale cascaded CNN for restoration of the pictures as well. We tried to increase the underwater images definitions by using proposed methods and modified adaptive histogram equalization which, still continues as the best.
Keywords: Fast Guided Filter, MSE, Multi-scale Cascaded CNN, PSNR, SSIM.
Scope of the Article: Image Security