Abstract
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.
Highlights
Improving the visibility in underwater images and videos is desirable for underwater robotics, photography/videography and species identification [1, 2, 3]
A key challenge is the spectral distortion in underwater scenes, which dehazing methods are unable to compensate for, especially for scenes captured at depth or in turbid waters (Fig. 1)
We presented a method for underwater image and video dehazing that avoids 385 the creation of artefacts in pure haze regions by automatically segmenting these areas and giving them an image or frame-specific transmission value
Summary
Improving the visibility in underwater images and videos is desirable for underwater robotics, photography/videography and species identification [1, 2, 3]. A key challenge is the spectral distortion in underwater scenes, which dehazing methods are unable to compensate for, especially for scenes captured at depth or in turbid waters (Fig. 1). At depth the distortion is caused by the 10 process of absorption where longer wavelengths (red) are highly attenuated and shorter wavelengths (green and blue) are more readily transmitted [5]. In turbid coastal waters constituents in the water reduce visibility and more readily increase the transmission of green hues [5]. Important parameters to be estimated for underwater dehazing are the veil ing light (i.e. the light that is scattered from underwater particles into the line of sight of a camera) and the transmission (i.e. a transfer function that describes the light that is not scattered by the haze and reaches the camera) [6]
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