Literature DB >> 26513783

An Underwater Color Image Quality Evaluation Metric.

Miao Yang, Arcot Sowmya.   

Abstract

Quality evaluation of underwater images is a key goal of underwater video image retrieval and intelligent processing. To date, no metric has been proposed for underwater color image quality evaluation (UCIQE). The special absorption and scattering characteristics of the water medium do not allow direct application of natural color image quality metrics especially to different underwater environments. In this paper, subjective testing for underwater image quality has been organized. The statistical distribution of the underwater image pixels in the CIELab color space related to subjective evaluation indicates the sharpness and colorful factors correlate well with subjective image quality perception. Based on these, a new UCIQE metric, which is a linear combination of chroma, saturation, and contrast, is proposed to quantify the non-uniform color cast, blurring, and low-contrast that characterize underwater engineering and monitoring images. Experiments are conducted to illustrate the performance of the proposed UCIQE metric and its capability to measure the underwater image enhancement results. They show that the proposed metric has comparable performance to the leading natural color image quality metrics and the underwater grayscale image quality metrics available in the literature, and can predict with higher accuracy the relative amount of degradation with similar image content in underwater environments. Importantly, UCIQE is a simple and fast solution for real-time underwater video processing. The effectiveness of the presented measure is also demonstrated by subjective evaluation. The results show better correlation between the UCIQE and the subjective mean opinion score.

Entities:  

Year:  2015        PMID: 26513783     DOI: 10.1109/TIP.2015.2491020

Source DB:  PubMed          Journal:  IEEE Trans Image Process        ISSN: 1057-7149            Impact factor:   10.856


  6 in total

1.  A Underwater Sequence Image Dataset for Sharpness and Color Analysis.

Authors:  Miao Yang; Ge Yin; Haiwen Wang; Jinnai Dong; Zhuoran Xie; Bing Zheng
Journal:  Sensors (Basel)       Date:  2022-05-07       Impact factor: 3.847

2.  Evolving deep convolutional neutral network by hybrid sine-cosine and extreme learning machine for real-time COVID19 diagnosis from X-ray images.

Authors:  Chao Wu; Mohammad Khishe; Mokhtar Mohammadi; Sarkhel H Taher Karim; Tarik A Rashid
Journal:  Soft comput       Date:  2021-05-10       Impact factor: 3.732

3.  Multi-scale fusion framework via retinex and transmittance optimization for underwater image enhancement.

Authors:  Tie Li; Tianfei Zhou
Journal:  PLoS One       Date:  2022-09-26       Impact factor: 3.752

4.  Deep Supervised Residual Dense Network for Underwater Image Enhancement.

Authors:  Yanling Han; Lihua Huang; Zhonghua Hong; Shouqi Cao; Yun Zhang; Jing Wang
Journal:  Sensors (Basel)       Date:  2021-05-10       Impact factor: 3.576

5.  Multi-strategy Gaussian Harris hawks optimization for fatigue life of tapered roller bearings.

Authors:  Ahmad Abbasi; Behnam Firouzi; Polat Sendur; Ali Asghar Heidari; Huiling Chen; Rajiv Tiwari
Journal:  Eng Comput       Date:  2021-08-03       Impact factor: 8.083

6.  Underwater Image Enhancement Based on Histogram-Equalization Approximation Using Physics-Based Dichromatic Modeling.

Authors:  Yan-Tsung Peng; Yen-Rong Chen; Zihao Chen; Jung-Hua Wang; Shih-Chia Huang
Journal:  Sensors (Basel)       Date:  2022-03-10       Impact factor: 3.576

  6 in total

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