International Journal of Advances in Applied Sciences (IJAAS) Vol. 7, No. 1, March 2018, pp. 38~45 ISSN: 2252-8814, DOI: 10.11591/ijaas.v7.i1.pp38-45  38 Journal homepage: http://iaescore.com/online/index.php/IJAAS A Fusion Based Visibility Enhancement of Single Underwater Hazy Image Samarth Borkar, Sanjiv V. Bonde Department of Electronics and Telecommunication Engineering, Shri. Guru Gobind Singhji Institute of Engineering and Technology, SRTMUN University, India Article Info ABSTRACT Article history: Received May 21, 2017 Revised Jan 23, 2017 Accepted Feb 11, 2018 Underwater images are prone to contrast loss, limited visibility, and undesirable color cast. For underwater computer vision and pattern recognition algorithms, these images need to be pre-processed. We have addressed a novel solution to this problem by proposing fully automated underwater image dehazing using multimodal DWT fusion. Inputs for the combinational image fusion scheme are derived from Singular Value Decomposition (SVD) and Discrete Wavelet Transform (DWT) for contrast enhancement in HSV color space and color constancy using Shades of Gray algorithm respectively. To appraise the work conducted, the visual and quantitative analysis is performed. The restored images demonstrate improved contrast and effective enhancement in overall image quality and visibility. The proposed algorithm performs on par with the recent underwater dehazing techniques. Keyword: Color constancy Contrast enhancement Image dehazing Image fusion Underwater image restoration Copyright © 2018 Institute of Advanced Engineering and Science. All rights reserved. Corresponding Author: Samarth Borkar, Computer Vision and Pattern Recognition lab. Department of Electronics and Telecommunication Engineering, Shri. Guru Gobind Singhji Institute of Engineering and Technology, Vishnupuri - Nanded, Maharashtra, 431606, India. Email: borkarsamarth@sggs.ac.in 1. INTRODUCTION Underwater images are inherently dark in nature are also plagued by various small suspending particles and marine snow in an aqueous medium. To increase the visibility range and vision depth, an artificial light is utilized. The rays of light are scattered by particles in the underwater medium and along with color attenuation results in problems such as contrast reduction, blurring of an image and color loss driving the images beyond recognition. For underwater applications such as observation of the oceanic floor, monitoring of fish, study of coral reef etc. demands dehazing of images so as to recover color, enhance visibility and increase visual details present in the degraded image for computer vision and object recognition. In absence of any dehazing technique, the performance and usability of a standard enhancement algorithm may fail to produce desirable results. Basically, dehazing is a process to restore the contrast of an image. Traditional approaches like histogram equalization, histogram specification, and various other contrast enhancement techniques do not deliver desired output images. Over the last few years, diverse techniques have been proposed to restore the underwater hazy images. The dehazing approaches can be grouped into software based and hardware based. Hardware based techniques refer to utilization of polarization filter [1], range gated imaging [2] and using multiple underwater images [3], whereas software based techniques are further grouped into a physical model based and non-physical models. In physical model underwater image processing, parameters of the model are estimated and then restoration is achieved. Estimating the depth of underwater haze is the major hindrance in such models.