An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging

Wang, Yan; Song, Wei; Fortino, Giancarlo; Qi, Lizhe; Zhang, Wenqiang; Liotta, Antonio

doi:10.1109/access.2019.2932130

Cited by 220 publications

(130 citation statements)

References 116 publications

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“…The code of SMBLO, Dehaze-Net, MIL, and UWHL are available and released by authors on Github, and the code of MIP, UDCP, BGCD&RCC, IBLA, and ULAP used for comparison experiments are provided by Wang et al in [33].…”

Section: Resultsmentioning

confidence: 99%

Underwater Single Image Dehazing Using the Color Space Dimensionality Reduction Prior

et al. 2020

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Underwater images suffer from low visibility and contrast caused by absorption and scattering, which leads to haze and some further limitations. The existing underwater single image dehazing methods cannot achieve a balance between the performance and computational complexity, and are difficult to produce satisfactory results in the regions with large distance. To overcome these problems, we propose a new underwater single image dehazing method, which includes an improved background light estimation based on the quad-tree subdivision iteration algorithm, and a novel transmission estimation method. For the background light estimation, we introduce a robust score for each region of the image, which can evaluate the region from both smoothness and color. For the transmission estimation, we propose the color space dimensionality reduction prior (CSDRP), which allows conversing an image from the three-dimensional RGB color space to a 2D color space, namely the UV color space. In the UV color space, by clustering the pixels into mounts of haze-lines and carefully setting the haze-free boundary, the transmission map can be figured out and used to produce an excellent dehazed image. Experimental results show that our method has competitive effects compared with mainstream underwater single image dehazing methods. INDEX TERMS Underwater image dehazing, contrast enhancement, image enhancement, scattering removal.

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Section: Resultsmentioning

confidence: 99%

Underwater Single Image Dehazing Using the Color Space Dimensionality Reduction Prior

et al. 2020

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“…The underwater imaging theory and underwater images enhancement or restoration methods have been widely studied these years [5][6][7]. Retinex-based methods and histogram transform based algorithms are commonly used for underwater image enhancement.…”

Section: Introductionmentioning

confidence: 99%

Color Correction Based on CFA and Enhancement Based on Retinex With Dense Pixels for Underwater Images

Tang

Kwan

et al. 2020

IEEE Access

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Color correction and enhancement for underwater images is challenging due to attenuation and scattering. The underwater images often have low visibility and suffer from color bias. This paper presents a novel color correction method based on color filter array (CFA) and an enhancement method based on Retinex with dense pixels and adaptive linear histogram transformation for degraded color-biased underwater images. For any digital image in the RGB space, which is captured by digital camera with CFA, their RGB values are dependent and coupled because of the interpolation process. So we try to compensate red channel attenuation of underwater degraded images from the green channel and blue channel. Retinex model has been widely used to efficiently handle low brightness and blurred images. The McCann Retinex (MR) method selects a spiral path for pixel comparison to estimate illumination. However, the simple path selection doesn't include global light dark relationship of the whole image. So we design a scheme to gain much well-distributed and denser pixels to obtain more precise intensity of illumination. Besides, we design a piecewise linear function for histogram transform, which is adaptive to the whole RGB value. Experiments on a large number of underwater degraded images show that, the processed images by our method have clearer details and uniform visual effect for all channels in RGB color space and our method can also obtain good performance metrics. INDEX TERMS Underwater image enhancement, underwater image color correction, color filter array (CFA), Retinex, McCann Retinex, adaptive histogram transform.

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“…These methods use models to analyze the mechanism of underwater image degradation, and restore the images by reversing the degradation process and using model parameters deduced via prior knowledges. In these methods, the simplified image formation model (IFM) is frequently used for its effectiveness and simplicity [6], and due to its similarity to the model of outdoor hazy image, the Dark Channel Prior (DCP) from outdoor image dehazing [12] is also widely introduced in methods based on this model. In [13], Galdran et al proposed the Red Channel Prior based on the DCP to recover the lost contrast in underwater images.…”

Section: Introductionmentioning

confidence: 99%

“…In [14], Drews Jr et al proposed the Underwater DCP (UDCP) from the traditional DCP by To date, there have been many attempts to improve the quality of underwater images. According to recent literature reviews [6,7], they are usually classified into two main categories: underwater image enhancement and underwater image restoration. Methods of underwater image enhancement require no prior knowledge about the environment and mainly aim at improving the visual quality of underwater images.…”

Section: Introductionmentioning

confidence: 99%

An Underwater Image Enhancement Method for Different Illumination Conditions Based on Color Tone Correction and Fusion-Based Descattering

Liu

Shang

et al. 2019

Sensors

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In the shallow-water environment, underwater images often present problems like color deviation and low contrast due to light absorption and scattering in the water body, but for deep-sea images, additional problems like uneven brightness and regional color shift can also exist, due to the use of chromatic and inhomogeneous artificial lighting devices. Since the latter situation is rarely studied in the field of underwater image enhancement, we propose a new model to include it in the analysis of underwater image degradation. Based on the theoretical study of the new model, a comprehensive method for enhancing underwater images under different illumination conditions is proposed in this paper. The proposed method is composed of two modules: color-tone correction and fusion-based descattering. In the first module, the regional or full-extent color deviation caused by different types of incident light is corrected via frequency-based color-tone estimation. And in the second module, the residual low contrast and pixel-wise color shift problems are handled by combining the descattering results under the assumption of different states of the image. The proposed method is experimented on laboratory and open-water images of different depths and illumination states. Qualitative and quantitative evaluation results demonstrate that the proposed method outperforms many other methods in enhancing the quality of different types of underwater images, and is especially effective in improving the color accuracy and information content in badly-illuminated regions of underwater images with non-uniform illumination, such as deep-sea images.

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An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging

Cited by 220 publications

References 116 publications

Underwater Single Image Dehazing Using the Color Space Dimensionality Reduction Prior

Underwater Single Image Dehazing Using the Color Space Dimensionality Reduction Prior

Color Correction Based on CFA and Enhancement Based on Retinex With Dense Pixels for Underwater Images

An Underwater Image Enhancement Method for Different Illumination Conditions Based on Color Tone Correction and Fusion-Based Descattering

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