Spatio-temporal de-interlacing based on maximum likelihood estimation

Abstract

This paper proposes a novel de-interlacing algorithm that can make up motion compensation (MC) errors by using maximum likelihood (ML) estimator. Firstly, a proper registration is performed between current field and its adjacent fields, and the progressive frame corresponding to the current field is found via ML estimator based on the computed registration information. Here, in order to obtain a stable solution, well-known bilateral total variation (BTV)-based regularization is applied. Next, possible feathering artifacts are detected on a block basis effectively. So, edge-directional interpolation is applied to the pixels where feathering artifact may happen, instead of the above-mentioned temporal deinterlacing. Experimental results show that the PSNR of our proposed algorithm is on average 4dB higher than that of previous studies and provides the best visual quality.

Spatiotemporal deinterlacing using a maximuma posterioriestimator based on multiple-field registration

“…1 We can categorize the existing algorithms into three groups as follows: spatial deinterlacing, [2][3][4][5][6][7][8] motion-adaptive (MA) deinterlacing, [9][10][11] and motion compensation (MC)-based deinterlacing. [12][13][14][15][16][17][18][19][20][21][22] Spatial deinterlacing algorithms have the advantages of simple operation and straightforward integration into hardware. The edge-based line averaging (ELA) algorithm is one of the most popular deinterlacing algorithms in this category.…”

“…[13][14][15][16][17][18][19][20][21][22] For example, Chang et al presented an adaptive four-field global/local motion-compensated approach where the same parity four-field motion detection and four-field motion estimation detect static areas and fast motion by four reference fields, and global motion estimation detects camera panning and zooming motions. 13 However, this algorithm may give rise to feathering artifacts when the assumption of strong continuity of local motion does not work.…”

“…20. In this paper, we propose an advanced MAP-estimator-based deinterlacing algorithm using high-performance MC method and strong mode decision.…”