Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/3548
Title: Clustering Based Approach forUnderwater Sunlight Flicker Removal
Authors: Tripathy, Abhijeet
Singh, Malkhan
Haraprasad, Roy
Keywords: Caustic Noises
Image Processing
GMM Clustering
Artifact Removal
Issue Date: Nov-2020
Citation: Global Ocean , Oct-2020,Singapore-U.S. Gulf cost
Abstract: Computer vision-based approaches have been fre-quently deployed for AUV navigation, ecological surveys andstructural analysis of the seafloor. However, It undergoes sig-nificant distortions due to the specific propagation property oflight in underwater environments. It includes colour imbalance,non-uniform illuminance, low contrast and blurring effects. Apartfrom these limitations, sunlight flickers (caustic noises) are one ofthe prominent artefacts found on seafloor images in shallow waterenvironments. This noise decreases the efficiency of algorithmswhich exploit velocity estimation and image feature extraction,such as navigation and mapping algorithms for AUVs. Therefore,the removal of such noises becomes essential for better missionplanning and 3D Reconstruction of sea floor. In this paper, wepresent a novel online and computationally efficient algorithm forAUVs to minimize the sunlight flicker distortions in the framesduring the video survey. The primary benefit of the algorithmslies in the fact that it does not affect the non-flicker region. Hence,preserving the local features of the raw image and maintainingthe sharpness
Description: Copyright of this document is with publisher
URI: http://hdl.handle.net/2080/3548
Appears in Collections:Conference Papers

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