Search results for " Compression"
showing 10 items of 400 documents
Sparse Image Representation by Directionlets
2010
Despite the success of the standard wavelet transform (WT) in image processing in recent years, the efficiency and sparsity of its representation are limited by the spatial symmetry and separability of its basis functions built in the horizontal and vertical directions. One-dimensional discontinuities in images (edges or contours), which are important elements in visual perception, intersect too many wavelet basis functions and lead to a non-sparse representation. To capture efficiently these elongated structures characterized by geometrical regularity along different directions (not only the horizontal and vertical), a more complex multidirectional (M-DIR) and asymmetric transform is requi…
The Alternating BWT: an algorithmic perspective
2020
Abstract The Burrows-Wheeler Transform (BWT) is a word transformation introduced in 1994 for Data Compression. It has become a fundamental tool for designing self-indexing data structures, with important applications in several areas in science and engineering. The Alternating Burrows-Wheeler Transform (ABWT) is another transformation recently introduced in Gessel et al. (2012) [21] and studied in the field of Combinatorics on Words. It is analogous to the BWT, except that it uses an alternating lexicographical order instead of the usual one. Building on results in Giancarlo et al. (2018) [23] , where we have shown that BWT and ABWT are part of a larger class of reversible transformations, …
Balancing and clustering of words in the Burrows–Wheeler transform
2011
AbstractCompression algorithms based on Burrows–Wheeler transform (BWT) take advantage of the fact that the word output of BWT shows a local similarity and then turns out to be highly compressible. The aim of the present paper is to study such “clustering effect” by using notions and methods from Combinatorics on Words.The notion of balance of a word plays a central role in our investigation. Empirical observations suggest that balance is actually the combinatorial property of input word that ensure optimal BWT compression. Moreover, it is reasonable to assume that the more balanced the input word is, the more local similarity we have after BWT (and therefore the better the compression is).…
Tensor product multiresolution analysis with error control for compact image representation
2002
A class of multiresolution representations based on nonlinear prediction is studied in the multivariate context based on tensor product strategies. In contrast to standard linear wavelet transforms, these representations cannot be thought of as a change of basis, and the error induced by thresholding or quantizing the coefficients requires a different analysis. We propose specific error control algorithms which ensure a prescribed accuracy in various norms when performing such operations on the coefficients. These algorithms are compared with standard thresholding, for synthetic and real images.
An extension of the Burrows-Wheeler Transform and applications to sequence comparison and data compression
2005
We introduce a generalization of the Burrows-Wheeler Transform (BWT) that can be applied to a multiset of words. The extended transformation, denoted by E, is reversible, but, differently from BWT, it is also surjective. The E transformation allows to give a definition of distance between two sequences, that we apply here to the problem of the whole mitochondrial genome phylogeny. Moreover we give some consideration about compressing a set of words by using the E transformation as preprocessing.
Data Compression Using Wavelet and Local Cosine Transforms
2015
The chapter describes an algorithm that compresses two-dimensional data arrays, which are piece-wise smooth in one direction and have oscillating events in the other direction. Seismic, hyper-spectral and fingerprints data, for example, have such a mixed structure. The transform part of the compression process is an algorithm that combines wavelet and local cosine transform (LCT). The quantization and the entropy coding parts of the compression are taken from the SPIHT codec. To efficiently apply the SPIHT codec to a mixed coefficients array, reordering of the LCT coefficients takes place. On the data arrays, which have the mixed structure, this algorithm outperforms other algorithms that a…
The effect of wavelet and discrete cosine transform compression of digital radiographs on the detection of subtle proximal caries. ROC analysis.
2007
The study compared diagnostic performances of 2 different image compression methods: JPEG (discrete cosine transform; Joint Photographic Experts Group compression standard) versus JPEG2000 (discrete wavelet transform), both at a compression ratio of 12:1, from the original uncompressed TIFF radiograph with respect to the detection of non-cavitated carious lesions. Therefore, 100 approximal surfaces of 50 tooth pairs were evaluated on the radiographs by 10 experienced observers using a 5-point confidence scale. Observations were carried out on a standardized viewing monitor under subdued light conditions. The proportion of diseased surfaces was balanced to approximately 50% to avoid bias. Tr…
Fractional wavelet transform
1997
The wavelet transform, which has had a growing importance in signal and image processing, has been generalized by association with both the wavelet transform and the fractional Fourier transform. Possible implementations of the new transformation are in image compression, image transmission, transient signal processing, etc. Computer simulations demonstrate the abilities of the novel transform. Optical implementation of this transform is briefly discussed.
Testing the Acemoglu–Pischke model in Spain
2001
Abstract The Acemoglu–Pischke approach to training in imperfect labor markets predicts that wage compressions should shift incentives to invest in training from workers to firms. This will increase firm-sponsored general training when workers are unable to invest in training by themselves. Spain is on the top of the ranking of regulated labor markets. However, the training figures for Spain indicate a poor effect of highly compressed wage structure on firm-sponsored training.
Compression Methods for Microclimate Data Based on Linear Approximation of Sensor Data
2019
Edge computing is currently one of the main research topics in the field of Internet of Things. Edge computing requires lightweight and computationally simple algorithms for sensor data analytics. Sensing edge devices are often battery powered and have a wireless connection. In designing edge devices the energy efficiency needs to be taken into account. Pre-processing the data locally in the edge device reduces the amount of data and thus decreases the energy consumption of wireless data transmission. Sensor data compression algorithms presented in this paper are mainly based on data linearity. Microclimate data is near linear in short time window and thus simple linear approximation based …