IEEE Trans Image Process - Context coding of depth map images under the piecewise-constant image model representation.

Tópicos

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Resumo

This paper introduces an efficient method for lossless compression of depth map images, using the representation of a depth image in terms of three entities: 1) the crack-edges; 2) the constant depth regions enclosed by them; and 3) the depth value over each region. The starting representation is identical with that used in a very efficient coder for palette images, the piecewise-constant image model coding, but the techniques used for coding the elements of the representation are more advanced and especially suitable for the type of redundancy present in depth images. Initially, the vertical and horizontal crack-edges separating the constant depth regions are transmitted by 2D context coding using optimally pruned context trees. Both the encoder and decoder can reconstruct the regions of constant depth from the transmitted crack-edge image. The depth value in a given region is encoded using the depth values of the neighboring regions already encoded, exploiting the natural smoothness of the depth variation, and the mutual exclusiveness of the values in neighboring regions. The encoding method is suitable for lossless compression of depth images, obtaining compression of about 10-65 times, and additionally can be used as the entropy coding stage for lossy depth compression.

Resumo Limpo

paper introduc effici method lossless compress depth map imag use represent depth imag term three entiti crackedg constant depth region enclos depth valu region start represent ident use effici coder palett imag piecewiseconst imag model code techniqu use code element represent advanc especi suitabl type redund present depth imag initi vertic horizont crackedg separ constant depth region transmit d context code use optim prune context tree encod decod can reconstruct region constant depth transmit crackedg imag depth valu given region encod use depth valu neighbor region alreadi encod exploit natur smooth depth variat mutual exclus valu neighbor region encod method suitabl lossless compress depth imag obtain compress time addit can use entropi code stage lossi depth compress

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