Simultaneous underwater visibility assessment, enhancement and improved stereo

Abstract

Vision-based underwater navigation and obstacle avoidance demands robust computer vision algorithms, particularly for operation in turbid water with reduced visibility. This paper describes a novel method for the simultaneous underwater image quality assessment, visibility enhancement and disparity computation to increase stereo range resolution under dynamic, natural lighting and turbid conditions. The technique estimates the visibility properties from a sparse 3D map of the original degraded image using a physical underwater light attenuation model. Firstly, an iterated distance-adaptive image contrast enhancement enables a dense disparity computation and visibility estimation. Secondly, using a light attenuation model for ocean water, a color corrected stereo underwater image is obtained along with a visibility distance estimate. Experimental results in shallow, naturally lit, high-turbidity coastal environments show the proposed technique improves range estimation over the original images as well as image quality and color for habitat classification. Furthermore, the recursiveness and robustness of the technique allows implementation onboard an Autonomous Underwater Vehicle for improving navigation and obstacle avoidance performance.

Underwater Optical Image Processing: a Comprehensive Review

“…In general, these methods can be categorized into two approaches: hardware-based methods [5,6,7,8,9,10] and software-based methods [11,12,13,14]. There are four traditional hardware approaches to underwater imaging: polarization, range-gated imaging, fluorescence imaging [32,33], and stereo imaging [34]. Light has the properties of intensity, wavelength, and polarization.…”

Photometric Stereo in Participating Media Considering Shape-Dependent Forward Scatter

“…Several attempts have been made to design traditional 3D reconstruction techniques for participating media (e.g., structured light [11,4] and stereo [18,14]). Narasimhan et al [11] proposed a structured light method in participating media, and Gu et al [4] reconstructed the 3D shape of a participating medium using structured light.…”

Underwater image and video dehazing with pure haze region segmentation

“…Improving the visibility in underwater images and videos is desirable for underwater robotics, photography/videography and species identification ( Ancuti et al, 2012;Beijbom et al, 2012;Roser et al, 2014 ). While underwater conditions are considered by several authors as similar to dense fog on land, unlike fog, underwater illumination is spectrally deprived as water attenuates different wavelengths of light to different degrees ( Emmerson and Ross, 1987 ).…”