Low Complex Block Level Correlation and Registration for Video Frame Interpolation
In this paper, we propose a low complex block level correlation and registration for Video Frame
Interpolation (VFI) algorithm. The proposed method finds the correlation between the corresponding
non-overlapping blocks. The correlation coefficients indicate the amount of similarity between the
blocks. Using the median of correlation coefficients as threshold, the blocks are blended using image
registration process. Compared to existing block based Motion Compensated Frame Interpolation
(MCFI) methods, proposed algorithm is a low complex algorithm. In the proposed, there is no need
of Motion Estimation (ME), smoothing of unreliable Motion Vectors (MVs) and Motion Prediction.
Extensive experiments are conducted on various benchmark video sequences. Subjective assessment
shows that the artefacts like blocky artefacts, holes, blurry artefacts, and ghost effects in MCFI are
overcome by this algorithm, as there is no ME, preserving the true motion of the object to a greater
extent is possible. The metrics PSNR (Peak Signal to Noise Ratio) and SSIM (Structural Similarity
Index Metric) provide the objective assessment.
Author's Name: Brahmadesam T Madav, S.A.K. Jilani and S. Aruna Mastani
Volume: Volume 11
Issues: Volume 11
Keywords: PSNR (Peak Signal to Noise Ratio), SSIM (Structural Similarity Index Metric), Motion Compensated Frame Interpolation (MCFI).