An Interfield and Intrafield Weighted Interpolative Deinterlacing Algorithm Based on Low-Angle Detection and Multiangle Extraction

Abstract

In the process of converting interlaced scanning to progressive scanning, interline flickers, saw-tooth, and creeping could be found in motion images. This paper proposes an interfield and intrafield weighted interpolative algorithm based on low-angle detection and multiangle extraction. Using interframe difference of vertical edge area in current field and interfield difference of other areas as the input of motion detection, incorrect judgment could be avoided by four-fields motion detection so that static and motive image can be distinguished. Based on the motion image from the motion detection, multipixels are used in low-angle horizontal detection to extract higher correction angles so as to make interfield and intrafield weighted interpolation. The experiment results show that the proposed algorithm could improve peak signal-to-noise ratio (PSNR), restrain some interlace phenomenon, and reach better visual effects. Meanwhile, there is a good balance between efficiency and computation cost.

High-performance image deinterlacing using optical flow and artifact post-processing on GPU/CPU for surveillance and reconnaissance tasks

“…• Block matching based motion estimation 11,[18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34] • Edge direction dependent block based interpolation [35][36][37][38][39][40][41] • Edge direction dependent interpolation for example with adaptive distance weighting or based on second order image derivatives [42][43][44][45][46] • Gradient analysis with covariance matrices or tensors 47,48 • Using adaptive NL-means, bilateral or trilateral filters [49][50][51][52][53] • Dynamic time warping 54…”