基于梯度投影算法重构的压缩成像实验及质量评价

Compressed Imaging Experiments Based on Gradient Projection Algorithm Reconstruction and Image Quality Assessment

压缩成像方式既可以避免在红外波段追求大面阵器件,又可以解决图像获取时难以消除的自身非均匀性,信噪比低,航空航天成像应用中的图像采集、传输、存储成本越来越高等问题。详细分析了该成像系统的原理模型,搭建成像原理样机,采用梯度投影算法进行图像重构的成像实验。在重构图像的质量评价中引入了信号子空间分析方法,估计重构图像的信噪比。实验结果表明,该信噪比估计方法更加准确有效。

Compressed imaging avoids pursuing large array devices in infrared band, and it can solve problems like the heterogeneity which is difficult to eliminate during the image acquisition, low sound to noise ratio, higher and higher cost of acquiring, transmitting and storing images in the aerospace imaging applications and so on. The principle model of the compressed imaging system is analyzed in details, an imaging principle prototype is built, and the experiments of image reconstruction are conducted by the gradient projection algorithm. The signal subspace analysis is introduced in quality assessment of the reconstructed image to estimate the signal to noise ratio of the reconstructed image. Experimental results show that the proposed estimation method is more accurate and effective.