Hello, I am working as an Assistant Professor in Vellore Instititute of Technology, Tamilnadu. My research interest are in Image Processing, Computer vision and Deep Learning. I am currently working towards developing intelligent tools and techniques for single image dehazing in terrestrial, satellite, and underwater imaging.
Hazy environment attenuates the scene radiance and causes difficulty in distinguishing the color and texture of the scene. Traditional dehazing methods usually interpret the RGB value of the brightest region in haze images as the global air-light. In this paper, a new prior called ’color constancy prior’ has been proposed to improve the robustness of air-light estimation when varicolored illumination exists.
The images captured by Unmanned aerial vehicle system (UAVs) are often deteriorated by factors such as clouds occlusion, poor atmospheric illumination, and limited capability of the imaging system. To tackle problems, this paper presents a novel visibility restoration scheme for UAVs images by considering the following two assumptions: 1) The actual scene radiance of a UAVs image is bounded. 2) Pixels sharing the same appearance must have the same transmission value in a local neighborhood. Inspired by above assumptions, an image boundary constraint utilizing the median filter has been imposed on the RGB channel for the rough estimation of transmission-map in aerial images.
Images captured in underwater (UW) are often disturbed with several kind of degradation such as low visibility, non-uniform color cast, haze, and blurriness. To date, most UW image restoration methods have ignored the effects of sensor blur and noise. Therefore, in this paper, we propose a novel three stage algorithm for visibility recovery in UW images by considering both sensor blur and noise. In the first stage, blind deconvolution is used for the estimation of an unknown point spread function (PSF). In the second stage, a new prior called weighted median channel prior (WMCP) is used for the estimation of scene depth and background light. In the third stage, a color balancing (CB) module is adopted to minimize the effect of non-uniform color cast.
Single image dehazing is an ill-posed problem that requires assumptions, priors and constraints to solve. In this paper, boundary constraint utilizing median filter has been proposed on the image radiance for the rough estimation of transmission-map in haze images. Furthermore, for the refinement of estimated transmission-map, the proposed method use a multi-dimensional feature space that uses nearest neighborhood optimization under the framework of non-local principle.
