Compressed text indexes: From theory to practice
Journal of Experimental Algorithmics (JEA)
A New Point Access Method Based on Wavelet Trees
ER '09 Proceedings of the ER 2009 Workshops (CoMoL, ETheCoM, FP-UML, MOST-ONISW, QoIS, RIGiM, SeCoGIS) on Advances in Conceptual Modeling - Challenging Perspectives
| Hi-index | 0.00 |
Recent advances in compressed data structures have led to the new concept of self-indexing; it is possible to represent a sequence of symbols compressed in a form that enables fast queries on the content of the sequence. This paper studies different analogies of self-indexing on images. First, we show that a key ingredient of many self-indexes for sequences, namely the wavelet tree, can be used to obtain both lossless and lossy compression with random access to pixel values. Second, we show how to use self-indexes for sequences as a black-box to provide self-indexes for images with filtering-type query capabilities. Third, we develop a tailor-made self-index for images by showing how to compress two-dimensional suffix arrays. Experimental results are provided to compare the compressibility to standard compression methods.