Linear filtering of image subbands for low complexity postprocessing of decoded color images
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CitationBayazit, U. (2005). Linear filtering of image subbands for low complexity postprocessing of decoded color images. Proceedings of SPIE - the International Society for Optical Engineering, 5685(2), 810-820. doi:10.1117/12.586769
In , image adaptive linear minimum mean squared error (LMMSE) filtering was proposed as an enhancement layer color image coding technique that exploited the statistical dependencies among the luminance/chrominance or Karhunen Loeve Transform (KLT) coordinate planes of a lossy compressed color image to enhance the red, blue, green (RGB) color coordinate planes of that image. In the current work, we propose the independent design and application of LMMSE filters on the subbands of a color image as a low complexity solution. Towards this end, only the coordinates of the neighbors of the filtered subband coefficient, that are sufficiently correlated with the corresponding coordinate of the filtered subband coefficient, are included in the support of the filter for each subband. Additionally, each subband LMMSE filter is selectively applied only on the high variance regions of the subband. Simulation results show that, at the expense of an insignificant increase in the overhead rate for the transmission of the coefficients of the filters and with about the same enhancement gain advantage, subband LMMSE filtering offers a substantial complexity advantage over fullband LMMSE filtering.