Multiresolution-based Texture Adaptive Motion Detection for De-interlacing

Abstract

Motion-adaptive de-interlacing algorithm selects [4]. A more advanced technique to handle motion is motion from inter-field and intra-field interpolations according to estimation. Lee, Vissers and Liu [5] proposed a reducedmotion. Correct determination of motion information is complexity 3D motion estimation architecture which can be essential for this purpose. Fine textures, having high local used in MPEG4 and H.264.pixel variation, tend to cause false detection of motion. This paper proposed a texture detection mechanism utilizing In area of fine textures, which has high local variance or multiresolution technique to improve the correctness of frequency, pixels tend to have large gray level variation detection. A recursive 2-field algorithm is also proposed to within a small region. Slight motion or panning of camera reduce the memory cost in 4-field method. This algorithm would result in large pixel difference between two fields provides better perceptual visual quality than other motion which in turn causes erroneous motion detection. Detection adaptive de-interlacing as shown by theexperimental results.of this kind of texture can be used to set an adaptive threshold in motion detection to provide more accurate result.

Algorithm and architecture design for wide range ELA deinterlacer

“…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]. Finally, a high quality deinerlacer used multi-resolution analysis to analyze the texture content [6].…”