顺序小波包图像压缩感知方法

针对压缩感知中测量次数不确定的问题,提出了顺序小波包图像压缩感知方法.该方法选用小波包变换分解图像,降低信号稀疏度,将图像划分为大小相等的小波包系数块,利用小波包系数块数学期望与稀疏度之间的关系,对初始采样信号y0的长度进行预测;同时变长设置顺序压缩感知过程中采样信号y1,…,yn的长度,来减少解压缩端重构次数以及两端的通信次数,从而解决传统顺序压缩感知方法中存在的不足.实验表明该方法在重构次数和重构精度上优于传统顺序压缩感知方法.

Sequential Image Compressed Sensing Based on Wavelet Packet

Aiming at solving the problem of the times of measurements, a scheme of sequential compressed sensing based on wavelet packet was proposed. The wavelet packet transform was firstly employed and the image was decomposed into wavelet packet blocks with the same size. The length of the initial sampling signal was then estimated using the relationship between the mathematical expectation and the sparsity of wavelet packet blocks. Meanwhile, the lengths of sampling signals were set dynamically in order to reduce the reconstruction and communication overhead. The problem of uncertain times of measurements in the traditional compressed sensing was thus overcome. Experimental results show that our proposed scheme has less reconstruction times and lower reconstruction error than the existed ones.