3D TV will become a prominent technology in the next generation. In this paper, a depth image based rendering system is proposed from algorithm level to hardware architecture level. We propose a novel depth image based rendering algorithm with edge-dependent gaussian filter and interpolation to improve the rendered stereo image quality. Based on our proposed algorithm, a fully-pipelined depth image based rendering hardware accelerator is proposed to support real-time rendering. The proposed hardware accelerator is optimized in three steps. First, we analyze the effect of fixed point operation and choose the optimal wordlength to keep the stereo image quality. Second, a three-parallel edge-dependent gaussian filter architecture is proposed to solve the critical problem of memory bandwidth. Finally, we optimize the hardware cost by the proposed hardware architecture. Only 1/21 amounts of vertical PEs and 1/11 amounts of horizontal PEs is needed by the proposed folded edge-dependent gaussian filter architecture. Futhermore, by the proposed check mode, the whole Z-buffer can be eliminated during 3D image warping. In additions, the on-chip SRAMs can be reduced to 66.7 percent compared with direct implementation by global and local disparity separation scheme. A prototype chip can achieve real-time requirement under the operating frequency of 80 MHz for 25 SDTV frames per second (fps) in left and right channel simultaneously. The simulation result also shows the hardware cost is quite small compared with the conventional rendering architecture.