激光与光电子学进展, 2020, 57 (16): 161026, 网络出版: 2020-08-05
基于拉普拉斯算子先验项的水下图像复原 下载: 1250次
Underwater Image Restoration Based on a Laplace Operator Prior Term
海洋光学 水下图像复原 水下光学成像模型 拉普拉斯算子 变分模型 oceanic optics underwater image restoration underwater optical image formation model Laplace operator variational model
摘要
由于水体及水中的悬浮粒子对光的吸收和散射作用,水下观测到的图像呈现出模糊、对比度低、噪声严重等问题,加大了水下图像分析与理解的难度。为了克服这些缺陷,以水下光学成像模型为基础,提出了一种基于拉普拉斯算子先验项的,可同时去雾、去噪的快速变分复原方法。首先,根据水下光学成像模型设计变分模型的数据项和规则项,对拟恢复图像采用拉普拉斯算子先验项作为变分能量方程的规则项。然后,采用改进后的红通道先验估计得到全局背景光,结合红通道先验估计得到每个通道的透射率图。为进一步提高计算效率,引入交替方向乘子法(ADMM)对所提出的模型进行交替优化迭代求解。实验结果表明,该算法能有效地去除水雾,抑制水下图像的噪声,提高图像的对比度和清晰度。
Abstract
Images captured underwater often suffer from haze, noise, and low contrast owing to the absorption and scattering of water and suspended particles, making it difficult for analysis and understanding. To overcome these limitations, combined with an underwater optical image formation model, a fast variational approach based on a Laplace operator prior term is proposed herein to simultaneously perform dehazing and denoising. Based on the underwater optical image formation model, the data and regular items of the unified variational model are designed, wherein the Laplacian operator prior term is adopted as the regular term. The prior estimation of the improved red channel and the underwater red channel are used to obtain the global background light and the transmission map, respectively. To further accelerate the whole progress, a fast alternating direction multiplier method (ADMM) is introduced to solve the energy function. Our proposed variational method based on the Laplace operator prior term is executed on a set of representative real underwater images, demonstrating that it can successfully remove haze, suppress noise, and improve contrast and visibility.
李景明, 侯国家, 潘振宽, 刘玉海, 赵馨, 王国栋. 基于拉普拉斯算子先验项的水下图像复原[J]. 激光与光电子学进展, 2020, 57(16): 161026. Jingming Li, Guojia Hou, Zhenkuan Pan, Yuhai Liu, Xin Zhao, Guodong Wang. Underwater Image Restoration Based on a Laplace Operator Prior Term[J]. Laser & Optoelectronics Progress, 2020, 57(16): 161026.