A Polynomial Approximation Motion Estimation Model for Motion-Compensated Frame Interpolation

Motion-compensated frame interpolation (MCFI) usually finds the most matched blocks by minimizing pixel intensity discrepancies between neighboring frames along the motion trajectory. However, the quality of interpolated frames is susceptible to inaccurate motion vectors possibly for regions with complex texture patterns, irregularly shaped objects, repeated patterns, motion blurring or aliasing, and so on. It is believed that pixel intensity across adjacent frames varies gradually and smoothly, and therefore can be modeled mathematically by a continuous and differentiable function. Thus, the pixel intensity within one frame can be expressed as either a forward polynomial approximation (FWPA) or a backward polynomial approximation (BWPA) by the Taylor expansion in this paper. The discrepancy between the FWPA and BWPA is employed to find the best motion vector. In addition, a motion-aligned partial derivative is proposed to calculate the Taylor expansion along the motion trajectory. The proposed method is applicable to any existing MCFI schemes and achieve superior performance by consuming relatively more buffer memories and computational resources. Extensive experimentation with comparison with previous techniques validates our method in terms of both objective and subjective criteria.