摘要
由于水体对光线的吸收和散射,造成水下对空所成图像噪声较大,对比度较低,降低了图像的观察效果。在前期研究工作中采用的去噪和对比度拉伸算法没有利用图像的深度信息,使增强后图像边缘细节不够突出。将深度信息引入水下对空图像去噪及对比度拉伸过程中,采用基于深度约束的均值去噪和基于深度感知的对比度拉伸算法处理水下对空图像,有效提升了水下对空图像的深度层次感及对象边缘的质量,为后期水下对空成像的目标探测和识别奠定了理论与技术基础。
Due to water body absorption and scattering of light,water to air imaging noise is to some extend high and the contrast of scene picture is always low.In this case,the viewing effect of the scene is greatly affected.Image depth information was not taken into account for image denoising and contrast stretching algorithms in the former research work,and this makes the enhanced image edge details not to be sufficient.In this paper,the depth information is introduced into image denoising and contrast stretching,and depth-constrained based mean denosing and depth-aware based contrast stretching algorithm are used to process water to air image which effectively improves the depth of water to air imaging and the quality of the edge of the object.It forms theory and technology foundation for target detection and recognition of water to air imaging.
作者
刘勇
于佳卉
李亚鹏
LIU Yong;YU Jia-hui;LI Ya-peng(PLA 91977 Force,Beijing 100036,China;Beijing No.35 High School,Beijing 100032,China;Huazhong Institute of Electro-Optics-Wuhan National Laboratory for Optoelectronics,Wuhan 430223,China)
出处
《光学与光电技术》
2019年第2期55-58,共4页
Optics & Optoelectronic Technology
基金
海装预研(7301×××)资助项目
关键词
水下对空图像
对比度拉伸
深度感知
图像去噪
图像增强
water to air imaging
contrast stretching
depth perception
image denoising
image enhancement
