基于自适应分块的高光谱图像压缩感知重构方法  

Compressed Sensing Reconstruction of Hyperspectral Images Based on Adaptive Blocking

作　　者：王洋[1] 杨孟宇 赵首博 WANG Yang;YANG Mengyu;ZHAO Shoubo(School of Measurement and Control Technology and Communication Engineering,Harbin University of Science and Technology,Harbin 150080,China;School of Mechanical and Power Engineering,Guangdong Ocean University,Zhanjiang 524000,China)

机构地区：[1]哈尔滨理工大学测控技术与通信工程学院,哈尔滨150080 [2]广东海洋大学机械与动力工程学院,湛江524000

出　　处：《电子与信息学报》2023年第7期2605-2613,共9页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(61801148);黑龙江普通本科高等学校青年创新人才培养计划(UNPYSCT-2020187)。

摘　　要：在对高光谱图像采样重构的研究中,整体采样和固定分块采样没有考虑到高光谱图像复杂的纹理特征分布,使用了相同的测量矩阵导致图像的重构质量较差。针对此问题,该文提出基于2维图像熵自适应分块压缩感知重构方法(ABCS-IE),该方法以图像2维熵作为高光谱图像纹理细节的度量,根据图像的纹理细节分布自适应改变图像子块的大小,然后为不同的图像块分配特定的采样值,根据分配的采样值设计专有的测量矩阵对图像块进行压缩测量,将采样测量值代入重构算法中进行重构。实验结果表明,与整体采样重构和固定分块采样重构相比,将该方法应用到压缩感知重构算法中对高光谱图像进行采样重构后,重构的图像在视觉效果上有明显的提高,取得的峰值信噪比(PSNR)和结构相似度(SSIM)最大,采样率为0.4时,PSNR提高了2~4 dB,SSIM最大提高了0.27,均方根误差(RMSE)和信息熵差值(ΔH)也有所降低,说明重构的图像更加接近原始图像。而且运算时间也减少了1~1.5 s。可见,该方法能充分利用高光谱图像的纹理特征,有效提高图像的重构质量,同时减少重构的运算时间。In the study of sampling and reconstruction of hyperspectral images,global sampling and fixed block sampling do not take into account the complex texture distribution of hyperspectral images,and the use of the same measurement matrix results in poor image reconstruction quality.To solve this problem,an Adaptive Block Compressed Sensing-Image Entropy(ABCS-IE)is presented.In this method,2-dimensional image entropy is used as a measure of texture details of hyperspectral images.The size of image blocks is adaptively changed according to the texture details distribution of the image.Then,specific sampling values are assigned to different image blocks,and a special measurement matrix is designed to compress the image blocks according to the assigned sampling values,and the sampled measurements are brought into the reconstruction algorithm for reconstruction.The experimental results show that when this method is applied to the compression-aware reconstruction algorithm to sample and reconstruct the hyperspectral image,the visual effect of the reconstructed image is significantly improved.The maximum Peak Signal-to-Noise Ratio(PSNR)and Structural SIMilarity(SSIM)are obtained.When the sampling rate is 0.4,the PSNR is increased by 2~4 dB and the SSIM is increased by 0.27,the Root Mean Square Error(RMSE)and the information entropy difference(ΔH)are also reduced,indicating that the reconstructed image is closer to the original image.Moreover,the operation time is reduced by 1~1.5 s.It can be seen that this method can make full use of texture features of hyperspectral images and improve effectively the quality of image reconstruction,and reduce the operation time of reconstruction.

关 键 词：高光谱图像重构 自适应分块 压缩感知 图像2维熵 

分 类 号：TN911.73[电子电信—通信与信息系统] TP751[电子电信—信息与通信工程]