Underwater image enhancement by dehazing and color correction

Abstract

Poor visibility due to the effects of light absorption and scattering is challenging for processing underwater images. We propose an approach based on dehazing and color correction algorithms for underwater image enhancement. First, a simple dehazing algorithm is applied to remove the effects of haze in the underwater image. Second, color compensation, histogram equalization, saturation, and intensity stretching are used to improve contrast, brightness, color, and visibility of the underwater image. Furthermore, bilateral filtering is utilized to address the problem of the noise caused by the physical properties of the medium and the histogram equalization algorithm. In order to evaluate the performance of the proposed approach, we compared our results with six existing methods using the subjective technique, objective technique, and color cast tests. The results show that the proposed approach outperforms the six existing methods. The enhanced images, as a result of implementing the proposed approach, are characterized by relatively genuine color, increased contrast and brightness, reduced noise level, and better visibility. Li, and Guo: Underwater image enhancement by dehazing and color correction Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 07/03/2015 Terms of Use: http://spiedl.org/terms Journal of Electronic Imaging 033023-3 May∕Jun 2015 • Vol. 24(3) Li, and Guo: Underwater image enhancement by dehazing and color correction Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 07/03/2015 Terms of Use: http://spiedl.org/terms Journal of Electronic Imaging 033023-5 May∕Jun 2015 • Vol. 24(3) Li, and Guo: Underwater image enhancement by dehazing and color correction Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 07/03/2015 Terms of Use: http://spiedl.org/terms underwater images (single fish, multiple fish_a, and multiple_fish_b), (b) Gray World (GW)'s results, (c) white balance (WB)'s results, (d) automatic white balance (AWB)'s results, (e) white patch Retinex (WPR)'s results, (f) McCann Retinex (MCR)'s results, (g) contrast-limited adapt histogram equalization (CLAHE)'s results, and (h) results of our proposed approach.

Restoration and Enhancement of Underwater Under-Exposure Images with Detail-Preserving

“…Experiments have shown that although the color related to short wavelength can be enhanced, the method used is limited by the accuracy of the optical model and parameter estimation; Reference [5] proposed a Rayleigh-distributed color model fusion method, which not only reduced image noise, but also improved the contrast of the image to a certain extent, but led to excessive image enhancement; The enhancement method of underwater image based on defogging and color correction proposed in [6], although it solves the interference of noise and fog, however, there may also be problems with insufficient or excessive image enhancement; Reference [7] used a single underwater image restoration method by combining the blue-green channel and the red channel.…”

Single underwater image enhancement based on color cast removal and visibility restoration

“…As a result, the effects of haze from scattering and the distortion from color cast can be reduced. Li and Guo 22 proposed an underwater image-enhancement method based on a dehazing algorithm and a filtering algorithm. Serikawa and Lu 19 addressed the problems of scattering and color cast for underwater images by compensating the attenuation discrepancy along the propagation path.…”

Single underwater image restoration by blue-green channels dehazing and red channel correction

“…Chani and Isa [15] improved the contrast and reduced the noise of underwater images through integrated color model with Rayleigh distribution. Li and Guo [16] proposed an underwater image enhancement method based on dehazing and color correction. However, underwater image enhancement technique usually produces under-enhanced or over-enhanced regions because this kind of technique is not based on the underwater imaging model.…”