My ongoing research into underwater image enhancement has resulted in a novel algorithm for underwater image and video dehazing. This work was accepted for publication in a Special Issue on Vision and Computational Photography and Graphics in Computer Vision and Image Understanding (Impact Factor 2.498).
Underwater scenes captured by cameras are plagued with poor contrast and a spectral distortion, which are the result of the scattering and absorptive properties of water. In this paper we present a novel dehazing method that improves visibility in images and videos by detecting and segmenting image regions that contain only water. The colour of these regions, which we refer to as pure haze regions, is similar to the haze that is removed during the dehazing process. Moreover, we propose a semantic white balancing approach for illuminant estimation that uses the dominant colour of the water to address the spectral distortion present in underwater scenes. To validate the results of our method and compare them to those obtained with state-of-the-art approaches, we perform extensive subjective evaluation tests using images captured in a variety of water types and underwater videos captured onboard an underwater vehicle.