Vector-based postprocessing of MPEG-2 signals for digital TV receivers

Digital transmission of video signals and block-based coding/decoding schemes produce new artifacts such as blocking, dirty window, ringing and mosquite effects. These artifacts become worse with decreasing MPEG-2 data rates. Therefore the reduction of MPEG-artifacts becomes an attractive feature for digital TV-receivers. On the other hand an important feature for digital receivers is the performance of their postprocessing techniques such as object recognition, motion estimation, vector-based upconversion and noise reduction on MPEG-signals which are decoded in a receiver-based module called 'set top box'. In this paper different models dealing with the interaction between 'set top box' and digital receiver are discussed. Hereby the influence of MPEG-artifacts on postprocessing are presented. A vector-based upconversion algorithm which applied nonlinear center weighted median filters is presented. Assuming a 2-channel model of the human visual system with different spatio temporal characteristics, errors of the separated channels can be orthogonalized and avoided by an adequate splitting of the spectrum. Hereby a very robust vector error tolerant upconversion method which significantly improves the interpopulation quality is achieved. This paper describes also a concept for temporal recursive noise and MPEG-artifact filtering on TV images based on visual noise perception characteristics. Different procedures in the spatial subbands lead to results well matched to the requirements of the human visual system. Using a subband-based noise filter temporally non-correlated MPEG-artifacts can significantly be reduced. Image analysis using object recognition for video postprocessing becomes more important. Therefore a morphological, contour-based multilevel object recognition method which even stays robust in strongly corrupted MPEG-2 images is also introduced.