Abstract:Underwater images suffer from various quality degradation problems such as color cast, low contrast, and blurred details. To solve these issues, a novel underwater image enhancement method that can implement color correction, detail sharpening, and contrast enhancement in stages. In particular, the proposed method combines multi-channel color compensation with color correction. It solves detail blurring and low contrast by the Gaussian differential pyramid and the local contrast enhancement of contrast limited… Show more
“…As shown in Fig. 1, the scattering effect results in the degradation of visibility, e.g., poor contrast and veiled details [7][8][9][10][11]. The absorption effect refers to a phenomenon of selective attenuation of light, which generates color distortion in underwater images [12][13][14][15].…”
Underwater images typically present poor visibility, color distortion, and noise, which limit the application in several high-level tasks of image analysis. To address these corruptions, a novel method is proposed to reconstruct high-quality underwater images, which is designed by integrating imaging model with noise and variational framework. Specifically, an improved underwater imaging model is first introduced by separating noise from real underwater scene. Subsequently, the hazy curves of degraded colors are decomposed to estimate transmission map, and a color loss prior is employed to correct the transmission map. Moreover, a first-order gradient guided filter is proposed to refine the transmission map. An evaluation formula is designed by combining illumination, contrast, and color deviation priors to accurately search for the background region. Finally, a variational model is established to restore underwater images and suppress noise based on the improved imaging model and image priors. Experimental results validate that the proposed method surpasses several outstanding approaches, demonstrating its well effectiveness in improving contrast, correcting color, and suppressing noise.INDEX TERMS Underwater image restoration, variational framework, imaging model with noise.
“…As shown in Fig. 1, the scattering effect results in the degradation of visibility, e.g., poor contrast and veiled details [7][8][9][10][11]. The absorption effect refers to a phenomenon of selective attenuation of light, which generates color distortion in underwater images [12][13][14][15].…”
Underwater images typically present poor visibility, color distortion, and noise, which limit the application in several high-level tasks of image analysis. To address these corruptions, a novel method is proposed to reconstruct high-quality underwater images, which is designed by integrating imaging model with noise and variational framework. Specifically, an improved underwater imaging model is first introduced by separating noise from real underwater scene. Subsequently, the hazy curves of degraded colors are decomposed to estimate transmission map, and a color loss prior is employed to correct the transmission map. Moreover, a first-order gradient guided filter is proposed to refine the transmission map. An evaluation formula is designed by combining illumination, contrast, and color deviation priors to accurately search for the background region. Finally, a variational model is established to restore underwater images and suppress noise based on the improved imaging model and image priors. Experimental results validate that the proposed method surpasses several outstanding approaches, demonstrating its well effectiveness in improving contrast, correcting color, and suppressing noise.INDEX TERMS Underwater image restoration, variational framework, imaging model with noise.
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