Underwater image restoration using geodesic color distance and complete image formation model

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.

Experimental Results

Results of the proposed algorithm. (a) Input underwater images. (b) The estimated transmission maps in the blue channel. (c) The backscattering layers and (d) the scene layers. (e) The restored scene radiance and (f) the white balanced scene radiance.

Publication

Eunpil Park and Jae-Young Sim, “Underwater image restoration using geodesic color distance and complete image formation model,” IEEE Access, vol. 8, pp. 157918-157930, Aug. 2020.