基于仿人眼自适应调节的多光谱视觉图像处理方法

发布时间：2018-06-22 20:46

本文选题：仿生视觉 + 多光谱　；参考：《红外与激光工程》2017年09期

【摘要】：针对传统仿生视觉系统中目标图像获取单一性问题,提出一种仿人眼自适应调节的多光谱视觉成像技术。首先,通过改进的自动调焦算法使成像系统同时采集可见光高分辨率图像及近红外低分辨率图像。然后,对于多光谱成像系统中由于分光棱镜折射率不同导致的在固定焦距下,可见光和近红外图像清晰度有所不同的问题,采用改进的二代小波变换进行近红外图像增强,提高图像对比度,改善视觉效果。最后,搭建基于液体变焦透镜的多光谱实验系统验证自动调焦算法及图像增强算法的实际性能。实验结果表明:系统完成有效自动调焦的平均用时为756 ms。同时,近红外图像增强后其灰度方差函数值提高了79.4%,解决了对比度低和细节模糊的问题,最终实现自适应调节。
[Abstract]:Aiming at the singularity of target image acquisition in traditional bionic vision system, a multispectral visual imaging technique based on human eye adaptive adjustment is proposed. Firstly, the improved auto-focusing algorithm enables the imaging system to simultaneously collect high resolution image of visible light and low resolution image of near infrared. Then, for the problem that the clarity of the visible and near infrared images in the fixed focal length is different due to the different refractive index of the splitter prism in the multispectral imaging system, the improved second generation wavelet transform is used to enhance the near infrared image. Improve image contrast and visual effect. Finally, a multi-spectral experimental system based on liquid zoom lens is built to verify the actual performance of the auto-focusing algorithm and image enhancement algorithm. The experimental results show that the average time for the system to complete effective auto-focusing is 756 Ms. At the same time, the gray level variance function of NIR image is increased by 79.4 after enhancement, which solves the problems of low contrast and fuzzy details, and finally realizes adaptive adjustment.
【作者单位】：北京信息科技大学光电信息与仪器北京市工程研究中心;北京信息科技大学光电测试技术北京市重点实验室;
【基金】：教育部“创新团队发展计划”(IRT_16R07)
【分类号】：TP391.41

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