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动态测量的高光谱图像压缩感知
引用本文:闫歌,许廷发,马旭,张宇寒,王茜,谭翠媚.动态测量的高光谱图像压缩感知[J].中国光学,2018,11(4):550-559.
作者姓名:闫歌  许廷发  马旭  张宇寒  王茜  谭翠媚
作者单位:北京理工大学 光电学院 光电成像技术与系统教育部重点实验室, 北京 100081
基金项目:国家自然科学基金重大科学仪器专项(No.61527802)
摘    要:针对高光谱图像相邻波段之间具有强光谱相关性的特点,为了提高高光谱图像压缩感知的重构效果,本文提出一种利用边缘信息设计动态测量率的压缩感知算法。首先,通过随机投影的分块压缩感知方法对每个图像块以固定测量率采样,重构出单波段图像作为其他波段的先验信息,并对其提取出图像边缘区域;然后,根据每个图像块边缘信息的丰富程度来自适应分配测量值。在固定总测量数的前提下,对不同图像块分配不同的测量次数。最后,利用分配好的测量次数对其余波段进行采集和重构。仿真结果表明,在相同总测量数情况下,本文提出的动态测量算法重构出的高光谱图像质量(PSNR)与传统固定测量压缩感知策略相比提高了1~4 dB,相比较下的重构时间也减少,在成功重构高光谱图像的基础上更增强了细节处的图像质量。

关 键 词:高光谱图像  压缩感知  动态测量率  谱间相关性
收稿时间:2017-12-14

Hyperspectral image compression sensing based on dynamic measurement
YAN Ge,XU Ting-fa,MA Xu,ZHANG Yu-han,WANG Xi,TAN Cui-mei.Hyperspectral image compression sensing based on dynamic measurement[J].Chinese Optics,2018,11(4):550-559.
Authors:YAN Ge  XU Ting-fa  MA Xu  ZHANG Yu-han  WANG Xi  TAN Cui-mei
Institution:School of Optoelectronics, MOE Key Laboratory of Optoelectronic Imaging Technology and System, Beijing Institute of Technology, Beijing 100081, China
Abstract:Based on the strong spectral correlation between adjacent bands of hyperspectral images, we proposes a compressed sensing algorithm that uses edge information to design dynamic measurement rate to improve the reconstruction effect of compressive sensing in hyperspectral images. First, each image block is sampled at a fixed measurement rate by a random projection block-compressive sensing method, a single-band image is reconstructed as a priori information of other bands, and an image edge region is extracted therefrom; then, the measurement values are adaptively assigned according to the richness of the edge information of each image block. With a certain total number of measurements, different number of measurements is assigned to different image blocks. Finally, the remaining wave bands are collected and reconstructed with the assigned measurements. The simulation results show that under the same total number of measurements, the hyperspectral image quality(Peak Signal to Noise Ratio(PSNR)) reconstructed by the dynamic measurement algorithm proposed in this paper is 1-4 dB higher than the traditional fixed-measurement compressive sensing strategy. Moreover, the reconstruction time is also reduced, and the image quality at the detail is further enhanced based on the successful reconstruction of the hyperspectral images.
Keywords:hyperspectral image  compressive sensing  dynamic measurement rate  inter-spectral correlation
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