Fusion of multiscale gradient domain enhancement and gamma correction for underwater image/video enhancement and restoration

计算机科学 图像增强 水下 图像复原 领域(数学分析) 人工智能 计算机视觉 图像(数学) 融合 图像处理 地质学 数学 数学分析 语言学 海洋学 哲学
作者
Amarendra Kumar Mishra,Manjeet Kumar,Mahipal Singh Choudhry
出处
期刊:Optics and Lasers in Engineering [Elsevier]
卷期号:178: 108154-108154
标识
DOI:10.1016/j.optlaseng.2024.108154
摘要

Underwater images and video often suffer from poor visibility and color cast because light gets scattered and absorbed in water. To solve this problem, a novel method based on the fusion of multiscale gradient-domain enhancement and gamma correction is proposed for underwater images and video enhancement. Firstly, a white balance is used for color correction to the input underwater image and video. secondly, the color corrected underwater RGB images are converted to YCbCr color space. The Y-component of the image is decomposed into the base layer and detail layers using a Weighted Least Squares (WLS) filter. The base layer is enhanced by using gamma correction and detail layers are enhanced using the S-shape function in the gradient domain. The enhanced base layer and detail layers are fused. Finally, the fused image combined with Cb and Cr-component of YCbCr color space to obtained enhanced image. The proposed method has been implemented on the Underwater Image Enhancement Benchmark (UIEB) dataset, Underwater-45 (U45) dataset, and Dataset Real-world Underwater Video of Artifacts (DRUVA) based on the Peak Signal-to-Noise Ratio (PSNR), Structure Similarity Index Measure (SSIM), Measure of Enhancement (EME), Discrete Entropy (DE), Underwater Image Quality Measure (UIQM), and Underwater Color Image Quality Evaluation (UCIQE). To verify the efficacy of the proposed method, a qualitative and quantitative comparison has been conducted on the UIEB, U45, and DRUVA datasets. The result demonstrates that the proposed method outperforms the state-of-the-art method, in terms of PSNR, SSIM, EME, UIQM, and UCIQE parameters. Furthermore, the efficiency of proposed method tested on fog image and low illumination images.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
1秒前
旭宝儿发布了新的文献求助10
1秒前
安稳先生发布了新的文献求助10
1秒前
Gsyin发布了新的文献求助10
1秒前
2秒前
传奇3应助LC采纳,获得10
2秒前
2秒前
xingxing发布了新的文献求助10
3秒前
3秒前
3秒前
比奇堡派大星完成签到 ,获得积分20
3秒前
4秒前
4秒前
香蕉觅云应助hulin_zjxu采纳,获得10
4秒前
星辰大海应助旭宝儿采纳,获得10
5秒前
Yon发布了新的文献求助10
6秒前
完美世界应助马到成功采纳,获得10
6秒前
伶俐小凝完成签到,获得积分10
6秒前
契咯发布了新的文献求助10
6秒前
大个应助学习的小张采纳,获得10
6秒前
雪花君完成签到,获得积分10
6秒前
6秒前
FashionBoy应助醉书生采纳,获得10
7秒前
7秒前
7秒前
8秒前
8秒前
8秒前
xingxing完成签到,获得积分10
9秒前
9秒前
小墨应助魔幻的凝芙采纳,获得10
9秒前
10秒前
10秒前
10秒前
风趣丸子发布了新的文献求助30
10秒前
镘淳发布了新的文献求助10
10秒前
笑点低蜜蜂完成签到,获得积分10
11秒前
完美世界应助飘逸烨华采纳,获得30
11秒前
我是老大应助超级的三问采纳,获得30
11秒前
高分求助中
Sustainability in Tides Chemistry 2800
The Young builders of New china : the visit of the delegation of the WFDY to the Chinese People's Republic 1000
юрские динозавры восточного забайкалья 800
English Wealden Fossils 700
Chen Hansheng: China’s Last Romantic Revolutionary 500
XAFS for Everyone 500
COSMETIC DERMATOLOGY & SKINCARE PRACTICE 388
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3143246
求助须知:如何正确求助?哪些是违规求助? 2794391
关于积分的说明 7811052
捐赠科研通 2450640
什么是DOI,文献DOI怎么找? 1303909
科研通“疑难数据库(出版商)”最低求助积分说明 627144
版权声明 601386