Abstract
Underwater images suffer from different types of quality degradation, including haze, blur, low contrast, and color distortion, owing to light scattering and absorption. This article proposes a novel underwater image restoration algorithm based on the complete underwater image formation model (UIFM). Although the majority of the existing methods consider the direct transmission and backward scattering components only, this study, in addition, includes forward scattering in the UIFM. We estimate the transmission map based on the observation that the scene distance is inversely proportional to the geodesic color distance from the background light. We also approximate the point spread function in the forward scattering term to estimate the scene radiance more faithfully. Moreover, we obtain the optimal parameters of the UIFM required for transmission estimation and scene radiance restoration by minimizing a cost function composed of the sharpness, information loss, and dark background prior. The experimental results confirm that the proposed algorithm considerably improves the quality of the estimated transmission maps and restores scene radiance compared with the existing state-of-the-art methods.
Highlights
Underwater imaging systems are used in numerous applications, e.g., monitoring underwater environments, construction of underwater artificial facilities, and searching for and rescue of sunken ships
The experimental results demonstrate that the proposed algorithm can remove the quality degradation from underwater images and restore the original scene radiance
In this article, we proposed a novel underwater image restoration algorithm based on the complete underwater image formation model (UIFM)
Summary
Underwater imaging systems are used in numerous applications, e.g., monitoring underwater environments, construction of underwater artificial facilities, and searching for and rescue of sunken ships. Sim: Underwater Image Restoration Using Geodesic Color Distance and Complete Image Formation Model of light attenuation varies according to the wavelength of the light such that red is more rapidly attenuated than blue or green Both the ambient light and attenuated scene radiance cause color distortion such that that we typically see bluish or greenish underwater images. Underwater image restoration methods estimate the original scene radiance from an input image based on UIFM. The majority of the existing underwater image restoration methods estimate the related parameters based on simplified imaging models and/or assumptions, and frequently fail to remove the blur and haze artifacts completely. The experimental results demonstrate that the proposed algorithm estimates the transmission maps more faithfully and restores the original scene radiance more reliably compared with existing state-of-the-art methods.
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