为提高压缩感知图像的重构质量,提出了一种基于离散余弦变换(DCT)分频带压缩感知的平滑投影Landweber重构算法.该算法充分考虑了不同的DCT系数频带对重构图像质量有不同的影响,对图像进行分块DCT后,按照频带能量大小重新组织DCT系数,对能量大的频带分配大的采样率,通过分频带变采样率的随机矩阵实现随机观测,采用平滑滤波器消除块效应,由投影Landweber算法实现图像的重构.实验结果表明,与BCS-SPL和MS-BCS-SPL重构算法相比,文中提出的算法显著提高了重构图像的峰值信噪比.
In order to improve the reconstruction quality of compressed sensing images, a band-CS (Compressed Sensing) algorithm with smooth projection Landweber is proposed on the basis of discrete cosine transform (DCT). Since different DCT coefficient bands have different effects on the final image reconstruction quality, first, this algorithm divides an image into several blocks and carries out DCT for each block. Secondly, DCT coefficients are regrouped according to the band energy, and the band with higher energy is sampled by random matrix with greater sampling rate. Then, the blocking effect is eliminated by using a smoothing filter. Finally, the compressed sensing reconstruction of images is implemented by means of smooth projection Landweber. Experimental results show that, in comparison with BCS-SPL and MS-BCS-SPL algorithms, the proposed algorithm improves the peak signal-to-noise ratio of reconstructed images significantly.