A high-quality spatial-temporal content-adaptive deinterlacing algorithm

Abstract

This paper introduced a spatial-temporal contentadaptive algorithm, which can precisely select an appropriate interpolation technique for high-quality deinterlacing according to the spectral, edge-oriented and statistical features of local video content. Our algorithm employs a linear-phase statisticaladaptive vertical-temporal filter to deal with generic video scenes and adopts a modified edge-based line-averaging interpolation to efficiently recover moving edges. In addition, annoying flickering artifacts are efficiently suppressed by a flickering detection and a field-averaging filter. As a result, our algorithm outperforms other non-motion compensated methods in terms of objective PSNR and reveals more impressive subjective visual quality.

Algorithm and architecture design for wide range ELA deinterlacer

“…Spatial interpolation will be employed when motion is detected, otherwise temporal interpolation will be performed. [2] chose interpolation filter adaptively by analyzing the content. Edge-based Line Average (ELA) is another common non-linear technique searching the orientation with the highest correlation and interpolates the missing pixel along the detected direction [3]- [5], [13], [14].…”