The usage of video content has increased in past ten decades. As a result, increase in usage of commercial video coding standards called High Efficiency Video Coding (HEVC/H.265). A self-Adaptive N-depth Context Tree Weighting algorithm (SANDCTW) is proposed to overcome the limitations of Context tree weighting (CTW) method, which applied in CABAC know as Context Adaptive Binary Arithmetic Coding. This CABAC uses KT estimators and relies on beginning with the Bayesian approach to determine the true distribution of the next symbol to select for data compression. This approach is suitable only if the true distribution is stationary, the proposed SANDCTW that uses discounted KT estimators, which is suitable if the distribution is non-stationary and it reduces the computation and memory cost. Additionally, Block size sustained intra mode detection (BSSIMD) is proposed based on the mass-center and sub-sampling approach. In this approach, all correlation directions about the entire block associated to the intra-prediction mode and DC mode directions determined by using mass-center vector. Then, the modes corresponding to the determined directions selected as the best intra-prediction candidates during the intra-coding process for computing Rate-Distortion Optimization (RDO) with less complexity. The bit rate of 60–70 frames per second (fps) achieved in this technique based on the different block, size. Thus, the bit rate is also reduced significantly compared with the preceding H.265 standard.