High Efficiency video coding (HEVC) Encoder could give higher compression efficiency by offering 35 intra modes. However, this increases the complexity of the encoder due to more modes participate in the decision process. Therefore, it is necessary to build a fast and efficient intra prediction algorithm that is practical for real time application. Statistical properties of reference samples and the current intra block can be investigated to find out which modes will be efficient for the current block. Therefore, an adaptive and efficient modes selection model is presented in this paper. Firstly, intra modes are efficiently short listed by calculating the Euclidean distance between the statistical features of the reference samples and the current block. Secondly, an efficient MPM selection method is proposed that selects the modes for MPM by investigating the correlation between the neigh boring blocks and the current block. Experimental results demonstrate that average BD-Rate saving of the proposed approach is -0.11%, and BD-PSNR is improved by 0.0065%.

SATD (Sum of Absolute Transformed Difference) based cost function is adopted to reduce the complexity of HEVC (High Efficiency video coding) codec by selecting up to 8 intra modes for RDO (Rate Distortion Optimization) process. However, transform of all 35 modes, and RDO of 8 modes is bottleneck in intra mode complexity reduction. In this paper, a hybrid approach for reducing intra coding complexity is proposed. Firstly, DC mode is declared as the optimal mode whenever the variance of available reference pixels is zero. Secondly, working of RMD (Rough Mode Decision) is optimized by evaluating transform of fewer modes than 35 modes. Thirdly, modes list to RDO is refined using neigh boring modes correlation concept. Finally, an early PU split termination technique is proposed which compares RD of available sub-PUs to the RD of 2N×2N PU. Experimental results demonstrate that average time saving of the proposed approach is 40%, while the BD-Bit Rate increment is only 0:37%.