摘要：Since it is usually unknown the over-sampling and under-sampling of image sparse in image compression, thereby can not verify the merits of sampling and reconstruction algorithm. Therefore it studies the signal sparse K estimation method of compressive sensing and proposes the objective estimation algorithm based on PCA image sparse which combined forward projection transformation theory and principal component transformation (PCA) method. In this paper, it creates image sparse and a linear relationship between the variance of coefficient function through the elaboration of compressive sensing theory to PCA and under the assumption that the principal component transform coefficient is approximately normal function. Experimental results show that: the proposed algorithm possess advantages of fast, low complexity and so on
