Simple Source Code for Block Motion Vector Calculation Using Four-Step Search Algorithm

Calculating block motion vectors is a core step in video encoding, primarily used for inter-frame prediction to reduce temporal redundancy. The Four-Step Search algorithm, as a classic motion estimation method, significantly reduces computational complexity while maintaining accuracy.

Core Algorithm Logic Initial Search Point: The algorithm starts with the current frame's target block as the center, defining an initial symmetric search window in the reference frame. Four-Step Iteration Process: Step 1: Select 8 candidate points around the center with larger intervals (e.g., 4-pixel step size) and compute block matching errors using metrics like Sum of Absolute Differences (SAD) or Sum of Squared Differences (SSD). Subsequent Steps: The point with minimum error becomes the new center. The step size gradually reduces (typically to 2 pixels, then 1 pixel) through iterative searches until reaching the final 1-pixel step size, locating the optimal matching block. Motion Vector Output: The coordinate difference between the final matching block and the original block defines the motion vector.

Optimization Techniques Early Termination: If the error at any step falls below a predefined threshold, the search can terminate early to save computations. Hierarchical Search: Implementation can incorporate image pyramids for coarse-to-fine search strategy, further reducing computational load.

This algorithm effectively balances precision and efficiency, making it suitable for real-time applications with high performance requirements. The implementation typically involves nested loops for step size reduction and error comparison functions for SAD/SSD calculations.