光学与光电技术, 2019, 17 (2): 55, 网络出版: 2019-05-10   

基于深度感知的水下对空图像增强算法研究

Research on Water to Air Imaging Enhancement Algorithm Based on Deep Perception
作者单位
1 中国人民解放军91977部队, 北京 100036
2 北京市第三十五中, 北京 100032
3 华中光电技术研究所-武汉光电国家研究中心, 湖北 武汉 430223
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。
Abstract
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.

刘勇, 于佳卉, 李亚鹏. 基于深度感知的水下对空图像增强算法研究[J]. 光学与光电技术, 2019, 17(2): 55. LIU Yong, YU Jia-hui, LI Ya-peng. Research on Water to Air Imaging Enhancement Algorithm Based on Deep Perception[J]. OPTICS & OPTOELECTRONIC TECHNOLOGY, 2019, 17(2): 55.

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