TV-Wavelet-L1（TVWL1）model which consists of total-variation (TV) and wavelet regularization has great capability in image reconstruction. However, traditional algorithms solving the TVWL1 model for image reconstruction ignore the way of synthesis/analysis sparse representation. A new image reconstruction algorithm is thus proposed to solve TVWL1, where the original signal reconstruction problem is decomposed into multiple much simpler sub-problems which can be solved alternately. In addition, the analysis sparse representation is considered in a sub-problem. Experimental results demonstrate that the proposed algorithm can obviously improve both objective and subjective qualities of reconstruction images compared with the existing algorithms.