With the development of spectral imaging towards higher space resolution,higher spectral resolution and higher signal to noise ratio,some problems have appeared in the traditional spectral imager,for example,data acquisition quantity is too big, the resolution is affected by frame frequency and pixel size of detector,precise alignment is difficult for big caliber and long focus system,and hard to develop signal to noise ratio because of limited optics power.To solve the above problems,a single disper-sion spectral imager based on compressed coding is studied.Specially,for the lack of system realization and experiment verifica-tion at home,the designation,realization,mathematic model and reconstruction algorithm under multi-frame measurement are mainly studied,and the prototype testing and data processing are achieved.At last,some key problems still need to study,such as code error analysis,multi-model and multi-algorithm,system demarcation,and reconstruction evaluation.This imaging sys-tem is consisted of obj ect glass,coding template,dispersion element,collimating lens,focus lens and detector,and hyperspec-tral data was reconstructed by sparse reconstruction algorithm.There are many advantages in the new system,for example,a smaller data size due to the sparse sample of multi-information,a higher resolution because of code super-resolution,an easier implementation for lower hardware requirement,a higher optical energy usage because the code is instead of slit.The results show that the measurement is efficient,the design of prototype is proper,reconstruction algorithm and calibration method are accurate,the space information of alphabet HSI object is clear,and the spectral information of alphabet HSI object is accurate and closed to tungsten lamp spectral,so the system designation and engineering realization are feasible.%随着光谱成像技术向高空间分辨率、高光谱分辨率、高信噪比方向发展,传统的光谱成像系统面临着数据采集量过大的问题,同时,系统分辨率受探测器帧频与像元尺寸影响较大、大口径长焦距系统难于精密装调、系统能量受限引起信噪比提高困难.为了解决上述问题,研究了一种单色散压缩编码光谱成像系统,并针对国内压缩编码光谱成像系统工程实现与试验验证不足的问题,重点研究了该新系统的设计与实现,模板平移下的系统数学模型及多帧重构算法,并给出实际样机试验及数据处理结果.最后,根据试验情况,总结提出该新技术后续发展需重点关注的研究内容,包括编码模板误差分析,多维稀疏重构模型与算法,压缩编码光谱成像系统标定技术,重构算法/重构图谱评价技术.单色散压缩编码光谱成像系统通过编码、色散、甚至下采样,由探测器接收得到成像观测图像,然后,利用该成像数据,通过重构算法,得到目标光谱图像数据,其优点是低数据量采样、工程实现硬件要求减低、多通道高通量探测.相关研究结果表明,该系统获取的数据有效,样机设计合理,重构算法与标定方法较为准确,其得到的字母H SI目标光谱图像的空间信息清晰,光谱信息较为准确,符合钨灯光谱,其系统设计与实现具有工程可行性.
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