Open AccessEnhancing the Quality of Underwater Images using Fusion of sequential Filters and Dehazing
Author(s) -
M. Suganthy,
Shree Lakshmi,
S. Palanivel
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.24.12067
Subject(s) - underwater , artificial intelligence , computer science , computer vision , homomorphic filtering , peak signal to noise ratio , contrast (vision) , noise reduction , filter (signal processing) , wavelet , channel (broadcasting) , mean squared error , noise (video) , pattern recognition (psychology) , image (mathematics) , image enhancement , mathematics , geography , computer network , statistics , archaeology
Effectively analyzing underwater images and identifying any object under the water has become a difficult task. Generally, the factors affecting underwater images are uneven lighting, low contrast, blunt colors, and characteristics of an object based on absorption and scattering of light. The proposed technique involves applying white balancing and contrast enhancement to the original image. The combination of filters namely homomorphic filtering, wavelet denoising, bilateral filter , adaptive filters are used and applied sequentially on the degraded underwater images. The results obtained showed that the proposed algorithm works well in refining the underwater image attributes. Peak Signal to Noise Ratio (PSNR) and Mean Squared Error (MSE) are used to evaluate performance of the algorithm.