Open AccessUnderwater Image Enhancement using HOG and SIFT Method
Author(s) -
Ashima Gupta*,
Reecha Sharma
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.f8840.088619
Subject(s) - underwater , scale invariant feature transform , artificial intelligence , computer science , feature (linguistics) , computer vision , population , process (computing) , remote sensing , environmental science , image (mathematics) , geography , linguistics , philosophy , demography , archaeology , sociology , operating system
Capturing underwater images can be considered as form of art and collecting data of underwater environment which plays major role in the field of marine biology research, marine zoology and ecology study. It also plays a significant role in scientific missions such as analyzing marine life species, taking census of population and monitoring underwater biological environment. Underwater imaging also offers many other attractions such as aquatic plants and animals, different types and species of fishes, shipwrecks, coral reef and beautiful landscapes. But the captured images lack contrast and are hazy due to absorption and scattering. Thus the quality of the image gets deteriorated. The degraded underwater images can be enhanced using different methods. This research work proposed the white balancing technique and image blending process to improve the degraded images. The image blending can be done using the methods of feature matching. The features can be matched using HOG and SIFT methods. The proposed technique is implemented in MATLAB and results are analyzed in the terms of PSNR and MSE.