Underwater image quality enhancement through integrated color model with Rayleigh distribution

By A. A. Ghani, Nor Ashidi Mat Isa. Applied Soft Computing, 2015

304 citations recorded by the source corpus.

Subfields: Atomic and Molecular Physics, and Optics, Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/04d95ce5bd738b1d88e5007ad584d88ca67b5022

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atomic and Molecular Physics, and Optics

1. Wenqi Ren
2. Yudong Wang
3. Huan Gao
4. Huihui Yue
5. Jichang Guo
6. Chongyi Li
7. Risheng Liu

In Computer Vision and Pattern Recognition

1. Chongyi Li
2. Chunle Guo
3. Runmin Cong
4. Peixian Zhuang
5. Sam Kwong
6. Junhui Hou
7. Wenqi Ren
8. Saeed Anwar

In Media Technology

1. Runmin Cong
2. Chongyi Li
3. Peixian Zhuang
4. Junhui Hou
5. Risheng Liu
6. Hanyu Li
7. Ye-cai Guo
8. Chunle Guo

Citations in the corpus

• Underwater Image Enhancement by Dehazing With Minimum Information Loss and Histogram Distribution Prior (2016, unknown): “Chani and Isa's method significantly enhances contrast and minimizes under-enhanced and over-enhanced areas.”
• Using labeled data to evaluate change detectors in a multivariate streaming environment (2009, unknown): “FastSCNN [18] adopts the skip connection in the deep convolutional neural network and proposes a shallow learning module to downsam-ple for fast and efficient multi-branch low-level feature extraction.”
• Real-World Underwater Enhancement: Challenges, Benchmarks, and Solutions Under Natural Light (2019, background): “Ghani [22] minimizes under-enhanced and over-enhanced areas R Entropy, MSE, PSNR 7”
• Underwater Image Enhancement Using a Multiscale Dense Generative Adversarial Network (2020, background): “Furthermore, both suspended particles and water affect the scene contrast by reflecting light to the camera lenses [4].”
• Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embedding (2021, background): “Early attempts aim to adjust the pixel values for visual quality improvement, such as dynamic pixel range stretching [23], pixel distribution adjustment [24], and image fusion [9], [25], [26].”
• PUGAN: Physical Model-Guided Underwater Image Enhancement Using GAN With Dual-Discriminators (2023, background): “This adjustment is generally performed in the spatial domain, such as dynamic pixel range stretching [12], pixel distribution adjustment [13], and image fusion [14],”
• UIEC^2-Net: CNN-based Underwater Image Enhancement Using Two Color Space (2021, methodology): “[47] used RGB and HSV color spaces during histogram stretching process, and in 2017, Ghani et al.”