基于仿人眼自适应调节的多光谱视觉图像处理方法

Multispectral visual image processing method based on adaptive regulation of humanoid eye

  • 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 single character of target image acquisition in the traditional bionic vision system, multispectral visual image processing method based on adaptive regulation of humanoid eye was proposed. Firstly, the improved automatic focusing algorithm was used to collect the high resolution image of visible light and the low resolution image of near-infrared light. In the multispectral imaging system, there were different problems of visible and near-infrared image resolution under fixed focal length due to different refractive index of spectral prism. The improved two-generation wavelet transform was adopted to enhance the image contrast and improve the visual effect. Finally, the performance of automatic focus algorithm and image enhancement algorithm was verified by using a multi-spectral experimental device based on liquid zoom lens. The experimental results indicate that the average time of effective auto focusing system is 756 ms, and the gray variance function value increases by 79.4% after near infrared image enhancement, which solves the problem of low contrast and fuzzy details and realizes adaptive regulation.

     

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