WLMS-based Transmission Refined Self-Adjusted No Reference Weather Independent Image Visibility Improvement. Issue 3 (4th May 2022)

• Record Type: Journal Article
• Authors: Roy, Sangita; Chaudhuri, Sheli Sinha
• Is Part Of: IETE journal of research. Volume 68:Issue 3(2022)
• Page Start: 1635
• Page End: 1651
• Publication Date: 2022-05-04
• Subjects: WLMS -- Dehazing -- Edge preserving Smoothing -- Computer vision -- Computational complexity; Electronics -- Periodicals; Telecommunication -- Periodicals; Electronics; Telecommunication; Periodicals; 621.38
• DOI: 10.1080/03772063.2019.1662335
• Languages: English
• ISSNs: 0377-2063

Abstract

Abstract : Single image dehazing is an ill-posed, challenging issue out of several dehazing techniques due to its limited information. Transmission map is a crucial reference to retrieve the dehazed output. An attempt has been taken to remove artefacts in the depth map of the hazy image with Weighted Least Mean Square-based edge preserved smoothing technique which in turn estimate artifact-free transmission map. Original bright, clear, and natural image radiance is restored using refined transmission estimation and image recovery optical model developed and it has been showed to be effective in comparison with the state-of-the art techniques. Extensive experiments (quality and quantity) validate that the proposed technique is computationally less expensive, simple, and efficient. Computational complexity is linear or quasi-linear depending on the size of the image, O(n) or O(nlogn). In either case complexity is still lower than other state-of-the art techniques. The proposed algorithm is adaptable to remove different types of haze. Visible distance, as well as extinction coefficient of the medium of the hazy and recovered images, are also measured.