Since the pilot overhead using traditional channel estimation methods in the Reconfigurable Intelligent Surface （RIS）-assisted wireless communication systems is excessively high， a block sparseness based Orthogonal Matching Pursuit （OMP） channel estimation scheme was proposed. Firstly， according to the millimeter Wave （mmWave） channel model， the cascaded channel matrix was derived and transformed into the Virtual Angular Domain （VAD） to obtain the sparse representation of the cascaded channels. Secondly， by utilizing the sparse characteristics of the cascaded channels， the channel estimation problem was transformed into the sparse matrix recovery problem， and the reconstruction algorithm based on compressive sensing was adopted to recover the sparse matrix. Finally， the special row-block sparse structure was analyzed， and the traditional OMP scheme was optimized to further reduce pilot overhead and improve estimation performance. Simulation results show that the Normalized Mean Squared Error （NMSE） of the proposed optimized OMP scheme based on the row-block sparse structure decreases about 1 dB compared with that of the conventional OMP scheme. Therefore， the proposed channel estimation scheme can effectively reduce pilot overhead and obtain better estimation performance.