Feature-assisted threshold selection for all-zero block detection and its application to video coding optimization in H.264

All-zero blocks (AZB) denote blocks with all zero DCT coefficients after quantization. Early determination of AZB can avoid unnecessary DCT/Q/IQ/IDCT computation. Existing techniques in the literature primarily address more efficient thresholds for early determination of AZB. This paper deals with the selection of such thresholds based on low level features including motion activity and texture information. This aspect is then utilized to avoid any: (1) unnecessary quarter accuracy motion estimation, (2) unnecessary multiple reference frame motion estimation, and (3) unnecessary DCT/Q/IQ/IDCT computation. The developed approach has been applied to two different format video sequences CIF and QCIF. The results show that the computational complexity is significantly reduced while the video quality is maintained at a tolerable loss level.