Interframe Prediction Based Stationary Block Revalidation VBSME Using Full Search and Vector-driven Techniques

Full search (FS) motion estimation provides high accuracy but at high computational cost, while fast search methods introduce irregular, hardware-unfriendly patterns. This work proposes four adaptive FS-based VBSME algorithms that preserve FS regularity while reducing complexity through direction-driven search, adaptive block sizes, stationary block revalidation (SBR), and early termination using a spiral pattern.On CIF sequences, vector-driven VBSME with early termination reduces SAD computations by 53.9–-94.5%, while SBR improves PSNR by up to 1.39 dB. For 1080p video, SBR-based FS VBSME achieves higher PSNR than conventional FSBME, while SBR-based vector-driven VBSME delivers nearly 60% fewer SAD evaluations.