Underwater Image Enhancement Using an Integrated Colour Model

By Kashif Iqbal, R. A. Salam, A. Osman, A. Talib. 2007

436 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/f5f877290a40b2bf7517405b404d348f56d7f58f

How researchers see this paper

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

1. Wei Song
2. Yudong Wang
3. Yan Wang
4. Dongmei Huang
5. Jichang Guo
6. Huan Gao
7. Huihui Yue
8. Karen A. Panetta

Citations in the corpus

• Automatic Red-Channel underwater image restoration (2015, methodology): “Sat( − → I ) = max(IR, IG, IB) −min(IR, IG, IB) max(IR, IG, IB) (11)”
• A deep CNN method for underwater image enhancement (2017, background): “Image based algorithms [3] [4] [5] [6] [7] estimate the transmission map directly from captured underwater image and then use it for color correction and haze removal.”
• Enhancement of Underwater Images With Statistical Model of Background Light and Optimization of Transmission Map (2019, methodology): “Firstly, we collect over 2000 underwater images from the papers of [9]-”
• Human-Visual-System-Inspired Underwater Image Quality Measures (2016, background): “It is acknowledged that the histogram of a visually appealing image spanned over a wide range [29].”
• UIEC^2-Net: CNN-based Underwater Image Enhancement Using Two Color Space (2021, methodology): “Iqbal et al. [44], [45] used histogram stretching process on two different color spaces.”