Abstract
This work proposes to develop an underwater image enhancement method based on histogram-equalization (HE) approximation using physics-based dichromatic modeling (PDM). Images captured underwater usually suffer from low contrast and color distortions due to light scattering and attenuation. The PDM describes the image formation process, which can be used to restore nature-degraded images, such as underwater images. However, it does not assure that the restored images have good contrast. Thus, we propose approximating the conventional HE based on the PDM to recover the color distortions of underwater images and enhance their contrast through convex optimization. Experimental results demonstrate the proposed method performs favorably against state-of-the-art underwater image restoration approaches.
Highlights
Underwater exploration has progressed greatly due to underwater remotely operated vehicles (ROVs) mounted with underwater surveillance video cameras or event data recorders [1]
Since our approach is relevant to physics-based dichromatic modeling (PDM)-based restoration, we introduce these relevant methods here
Peng et al proposed a depth estimation method for underwater scenes based on image blurriness and light absorption (IBLA) [10], restoring underwater images
Summary
Underwater exploration has progressed greatly due to underwater remotely operated vehicles (ROVs) mounted with underwater surveillance video cameras or event data recorders [1]. HE tries to distribute intensity levels (IL) of an image uniformly across the available IL range through a transformation function calculated using the image cumulative distribution function (CDF) It works for general cases; the absorbed lights for underwater scenes make the images bluish or greenish, which may cause HE-based methods to under-enhance or over-enhance the images. Points closer to dark scenes are still dark because of the intensity of scattered light they experience is lower These traditional methods may still fail to restore red light for underwater images due to its long wavelengths and low frequencies, which attenuate faster underwater. The proposed method using the HE approximation based on the PDM considers the physics characteristics of nature images to make the color restoration consistent among pixels while keeping the distributions of image intensities uniform across the entire IL range for better contrast. It may not be enough for restoring underwater images because they do suffer low contrast but color distortions
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