Underwater Image Restoration and Enhancement Based on a Fusion Algorithm With Color Balance, Contrast Optimization, and Histogram Stretching

被引：34

作者：

Luo, Weilin ^{[1
]}

Duan, Shunqiang ^{[1
]}

Zheng, Jiwen ^{[1
]}

机构：

[1] Fuzhou Univ, Coll Mech Engn & Automat, Fuzhou 350108, Peoples R China

来源：

IEEE ACCESS | 2021年 / 9卷

关键词：

Image color analysis; Histograms; Image restoration; Attenuation; Wavelet transforms; Machine learning algorithms; Adaptation models; Underwater image; restoration; enhancement; color balance; contrast; histogram; dark channel prior; QUALITY ENHANCEMENT; MODEL;

D O I：

10.1109/ACCESS.2021.3060947

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A fusion algorithm is proposed for the restoration and enhancement of underwater images. Color balance, contrast optimization and histogram stretching are carried out. To alleviate the effect of color shift in an underwater image, the scalar values of R, G, B channels are renewed so that the distributions of the three channels in histogram are similar. Instead of refining the transmittance in dark channel prior based restoration, an optimized contrast algorithm is employed by which the optimal transmittance is determined. To further improve the brightness and contrast of underwater images, a histogram stretching algorithm based on the red channel is given. To verify the effectiveness of the proposed fusion algorithm, experimental underwater images are treated. Results show that the quality of underwater images is improved significantly, both in term of subjective visual effect and objective evaluation. The proposed underwater image processing strategy is also compared with some popular techniques. Comparison results indicate the advantage of the proposed strategy over others.

引用

页码：31792 / 31804

页数：13