Journal ArticleDOI
Underwater image enhancement and restoration based on local fusion
TLDR
Experimental results show that the proposed method could effectively balance color distortion and enhance edges of the degraded images and is superior to many state-of-the-art methods.Abstract:
Underwater imaging and image processing play important roles in oceanic scientific research. However, because the light is absorbed and scattered, the obtained underwater images are seriously degraded. Color distortion, low contrast, and detail (edge information) loss are the major problems of underwater images. We propose a method to solve these problems. First, a local adaptive proportion fusion algorithm is proposed to produce a color-balanced image, which is the first input image. Second, an edge-enhanced image is produced as the second input image. Third, a proportion fusion image is produced as the third input image. Finally, the image formation model-based local triple fusion method is used to merge these three input images and get the final result. Experimental results show that the proposed method could effectively balance color distortion and enhance edges of the degraded images. Subjective and objective evaluations show that our method is superior to many state-of-the-art methods.read more
Citations
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Journal ArticleDOI
Underwater Single Image Color Restoration Using Haze-Lines and a New Quantitative Dataset
TL;DR: This work places multiple color charts in the scenes and calculated its 3D structure using stereo imaging to obtain ground truth, and contributes a dataset of 57 images taken in different locations that enables a rigorous quantitative evaluation of restoration algorithms on natural images for the first time.
Journal ArticleDOI
Underwater image restoration: A state‐of‐the‐art review
Proceedings ArticleDOI
Unveiling Optical Properties in Underwater Images
TL;DR: This work focuses on robust estimation of the water properties, and as opposed to previous methods that used fixed values for attenuation, estimates the veiling-light color from objects in the scene, contrary to looking at background pixels.
Book ChapterDOI
An Enhancement of Underwater Images Based on Contrast Restricted Adaptive Histogram Equalization for Image Enhancement
Vishal Goyal,Aasheesh Shukla +1 more
TL;DR: In this article, an adaptive histogram equalization (AHE)-based new underwater image enhancement technique is proposed to get enhanced results by adjusting the spacing between two adjacent gray levels adaptively to take target function as information entropy.
Journal ArticleDOI
An efficient single image haze removal algorithm for computer vision applications
TL;DR: An effective haze removal algorithm is reported for removing fog or haze from a single image and it is shown that the proposed model is more efficient in comparison to the existing haze removal algorithms in terms of qualitative and quantitative analysis.
References
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Journal ArticleDOI
A Focus on Recent Developments and Trends in Underwater Imaging
TL;DR: Underwater optical imaging advances from 2005 to the present are reviewed in this article, where several recent novel system applications are given, as well as brief summaries of emerging underwater imaging research and development trends.
Journal ArticleDOI
WaterGAN: Unsupervised Generative Network to Enable Real-Time Color Correction of Monocular Underwater Images
TL;DR: WaterGAN as discussed by the authors is a generative adversarial network (GAN) for generating realistic underwater images from in-air image and depth pairings in an unsupervised pipeline used for color correction of monocular underwater images.
Journal ArticleDOI
Underwater Single Image Color Restoration Using Haze-Lines and a New Quantitative Dataset
TL;DR: This work places multiple color charts in the scenes and calculated its 3D structure using stereo imaging to obtain ground truth, and contributes a dataset of 57 images taken in different locations that enables a rigorous quantitative evaluation of restoration algorithms on natural images for the first time.
Journal ArticleDOI
Automatic Image Equalization and Contrast Enhancement Using Gaussian Mixture Modeling
Turgay Celik,Tardi Tjahjadi +1 more
TL;DR: An adaptive image equalization algorithm that automatically enhances the contrast in an input image that is free of parameter setting for a given dynamic range of the enhanced image and can be applied to a wide range of image types.
Journal ArticleDOI
Underwater image quality enhancement through integrated color model with Rayleigh distribution
TL;DR: Qualitative analysis reveals that the proposed method significantly enhances the image contrast, reduces the blue-green effect, and minimizes under- and over-enhanced areas in the output image.