Journal ArticleDOI
Color correction and adaptive contrast enhancement for underwater image enhancement
TLDR
This work designs the dedicated fractions to compensate the lower color channels and an adaptive contrast enhancement algorithm is applied to each color channel to produce the background-stretched and foreground-stretched images, which significantly improves the contrast of the output image.About:
This article is published in Computers & Electrical Engineering.The article was published on 2021-05-01. It has received 46 citations till now. The article focuses on the topics: Color correction & Unsharp masking.read more
Citations
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Journal ArticleDOI
Underwater Image Enhancement via Minimal Color Loss and Locally Adaptive Contrast Enhancement
TL;DR: Li et al. as discussed by the authors proposed an efficient and robust underwater image enhancement method, called MLLE, which adjusts the color and details of an input image according to a minimum color loss principle and a maximum attenuation map-guided fusion strategy.
Journal ArticleDOI
Retinex-inspired color correction and detail preserved fusion for underwater image enhancement
Wei Zhang,Lili Dong,Wenhai Xu +2 more
TL;DR: In this paper , a novel underwater image enhancement method based on Retinex-inspired color correction and detail preserved fusion technology is proposed to cope with color cast, blurring, and low contrast of underwater images for display and further analysis.
Journal ArticleDOI
A context hierarchical integrated network for medical image segmentation
TL;DR: Zhang et al. as discussed by the authors proposed a context hierarchical integrated network (CHI-Net) for medical image segmentation, which can accurately segment salient regions from medical images in a purely task-driven manner.
Journal ArticleDOI
Underwater Image Enhancement by Attenuated Color Channel Correction and Detail Preserved Contrast Enhancement
TL;DR: This article proposes an underwater image color correction method that employs a dual-histogram-based iterative threshold method and a limited histogram method with Rayleigh distribution to improve the global and local contrast of the color-corrected image, thus achieving a global contrast-enhanced version and a local Contrast enhanced version.
Journal ArticleDOI
MCI-Net: Multi-scale context integrated network for liver CT image segmentation
TL;DR: Wang et al. as mentioned in this paper proposed a multi-scale context integration network (MCI-Net) for liver image segmentation, which combines four cascaded branches of hybrid dilated convolutions to capture broader and deeper features.
References
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Proceedings ArticleDOI
Enhancing underwater images and videos by fusion
TL;DR: A novel strategy to enhance underwater videos and images that derives the inputs and the weight measures only from the degraded version of the image, and supports temporal coherence between adjacent frames by performing an effective edge preserving noise reduction strategy.
Journal ArticleDOI
An Underwater Image Enhancement Benchmark Dataset and Beyond
TL;DR: This paper constructs an Underwater Image Enhancement Benchmark (UIEB) including 950 real-world underwater images, 890 of which have the corresponding reference images and proposes an underwater image enhancement network (called Water-Net) trained on this benchmark as a baseline, which indicates the generalization of the proposed UIEB for training Convolutional Neural Networks (CNNs).
Journal ArticleDOI
Human-Visual-System-Inspired Underwater Image Quality Measures
TL;DR: A new nonreference underwater image quality measure (UIQM) is presented, which comprises three underwater image attribute measures selected for evaluating one aspect of the underwater image degradation, and each presented attribute measure is inspired by the properties of human visual systems (HVSs).
Journal ArticleDOI
An Underwater Color Image Quality Evaluation Metric
Miao Yang,Arcot Sowmya +1 more
TL;DR: In this article, a new underwater color image quality evaluation (UCIQE) metric is proposed to quantify the non-uniform color cast, blurring, and low contrast that characterize underwater engineering and monitoring images.
Journal ArticleDOI
Color Balance and Fusion for Underwater Image Enhancement
TL;DR: This work introduces an effective technique to enhance the images captured underwater and degraded due to the medium scattering and absorption by building on the blending of two images that are directly derived from a color-compensated and white-balanced version of the original degraded image.