Deblocking of block-transform compressed images using weighted sums of symmetrically aligned pixels
A new class of related algorithms for deblocking block-transform compressed images and video sequences is proposed in this paper. The algorithms apply weighted sums on pixel quartets, which are symmetrically aligned with respect to block boundaries. The basic weights, which are aimed at very low bit...
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 14(2005), 2 vom: 27. Feb., Seite 200-12 |
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| Weitere Verfasser: | , |
| Format: | Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2005
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Schlagworte: | Comparative Study Evaluation Study Journal Article Validation Study |
| Zusammenfassung: | A new class of related algorithms for deblocking block-transform compressed images and video sequences is proposed in this paper. The algorithms apply weighted sums on pixel quartets, which are symmetrically aligned with respect to block boundaries. The basic weights, which are aimed at very low bit-rate images, are obtained from a two-dimensional function which obeys predefined constraints. Using these weights on images compressed at higher bit rates produces a deblocked image which contains blurred "false" edges near real edges. We refer to this phenomenon as the ghosting effect. In order to prevent its occurrences, the weights of pixels, which belong to nonmonotone areas, are modified by dividing each pixel's weight by a predefined factor called a grade. This scheme is referred to as weight adaptation by grading (WABG). Better deblocking of monotone areas is achieved by applying three iterations of the WABG scheme on such areas followed by a fourth iteration which is applied on the rest of the image. We refer to this scheme as deblocking frames of variable size (DFOVS). DFOVS automatically adapts itself to the activity of each block. This new class of algorithms produces very good subjective results and PSNR results which are competitive relative to available state-of-the-art methods |
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| Beschreibung: | Date Completed 08.03.2005 Date Revised 10.12.2019 published: Print Citation Status MEDLINE |
| ISSN: | 1941-0042 |