Approaches to image compression and indexing based on extensions to 2D of some of the Lempel-Ziv incremental parsing techniques have been proposed in the recent past. In these approaches, an image is decomposed into a number of patches, consisting each of a square or rectangular solid block. This paper proposes image compression techniques based on patches that are not necessarily solid blocks, but are affected instead by a controlled number of undetermined or don't care pixels. Such patches are chosen from a set of candidate motifs that are extracted in turn from the image 2D motif basis, the latter consisting of a compact set of patterns that result from the autocorrelation of the image with itself. As is expected, it is found that limited indeterminacy can be traded for higher compression at the expense of negligible loss. Preliminary experiments show that this technique yields higher compression than other popular techniques such as GZip, BZip and Jpeg. © 2011 IEEE.
Image compression by 2D motif basis
Amelio A.;
2011-01-01
Abstract
Approaches to image compression and indexing based on extensions to 2D of some of the Lempel-Ziv incremental parsing techniques have been proposed in the recent past. In these approaches, an image is decomposed into a number of patches, consisting each of a square or rectangular solid block. This paper proposes image compression techniques based on patches that are not necessarily solid blocks, but are affected instead by a controlled number of undetermined or don't care pixels. Such patches are chosen from a set of candidate motifs that are extracted in turn from the image 2D motif basis, the latter consisting of a compact set of patterns that result from the autocorrelation of the image with itself. As is expected, it is found that limited indeterminacy can be traded for higher compression at the expense of negligible loss. Preliminary experiments show that this technique yields higher compression than other popular techniques such as GZip, BZip and Jpeg. © 2011 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
