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Underwater image restoration based on modified color-line model

机译:基于改进的颜色线模型的水下图像恢复

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摘要

Underwater images suffer from haze, color distortion, and low contrast due to the absorption and scattering of transmitted light. A systematic approach including accurate background light (BL) estimation and transmission (TM) estimation is proposed based on color-line model for underwater images restoration. The estimation of BL candidate region is improved by combining quadtree subdivision and minimum unary gray entropy evaluation, to realize a high-quality restoration and improve accuracy of TM estimation with color-line model. Given incomplete intersection of color lines with BL, a convex optimization function is proposed to improve accuracy of TM estimation. On the basis of restorations with BL and TM estimations, pixel distribution stretching and Unsharp Masking are employed to correct color and enhance edge information for better performance of vision. Comprehensive evaluations illustrate that the proposed method could efficiently restore underwater images with visibility improvement, natural color correction, and contrast enhancement. (C) 2021 SPIE and IS&T
机译:由于透射光的吸收和散射,水下图像遭受雾度,颜色变形和低对比度。基于用于水下图像恢复的颜色线模型提出了一种系统方法,包括精确的背景光(BL)估计和传输(TM)估计。通过组合Quadtree细分和最小的灰度熵评估来改善BL候选区域的估计,实现了高质量的恢复,提高了与彩线模型的TM估计的精度。给定与BL的彩色线路不完全交叉,提出了一种凸优化功能,提高TM估计的精度。在使用BL和TM估计的修复基础上,采用像素分布拉伸和遮蔽屏蔽来校正颜色并增强边缘信息以获得更好的视觉性能。综合评估说明所提出的方法可以有效地恢复具有可见性改进,自然色彩校正和对比度增强的水下图像。 (c)2021个SPIE和IS&T

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