Journal ArticleDOI
Improved techniques for single-pass adaptive vector quantization
C. Constantinescu,J.A. Storer +1 more
- Vol. 82, Iss: 6, pp 933-939
Reads0
Chats0
TLDR
Improvements in speed, simplicity of codebook entries, and visual quality with no loss in either the amount of compression or the SNR as compared to the original full-search version are presented.Abstract:
Constantinescu and Storer presented a new single-pass adaptive vector quantization algorithm that learns a codebook of variable size and shape entries; they presented experiments on a set of test images showing that with no training or prior knowledge of the data, for a given fidelity, the compression achieved typically equals or exceeds that of the JPEG standard. This paper presents improvements in speed (by employing K-D trees), simplicity of codebook entries, and visual quality with no loss in either the amount of compression or the SNR as compared to the original full-search version. >read more
Citations
More filters
Journal ArticleDOI
A suboptimal lossy data compression based on approximate pattern matching
TL;DR: For stationary mixing sequences, the problem investigated by Steinberg and Gutman by showing that a lossy extension of the Wyner-Ziv (1989) scheme cannot be optimal is settled, and the asymptotic behavior of the so-called approximate waiting time N/sub l/ is established.
Journal ArticleDOI
Lossless compression of continuous-tone images
TL;DR: In this paper, the authors survey some of the recent advances in lossless compression of continuous-tone images and discuss the modeling paradigms underlying the state-of-the-art algorithms, and the principles guiding their design.
Journal ArticleDOI
Multidimensional signal compression using multiscale recurrent patterns
TL;DR: A theoretical analysis of the approximate matching of Gaussian vectors using scales is given, which gives a justification of why approximate multiscale matching is a good option, specially at low rates.
Journal ArticleDOI
Pattern matching image compression: algorithmic and empirical results
TL;DR: The main idea behind the PMIC is a lossy extension of the Lempel-Ziv data compression scheme in which one searches for the longest prefix of an uncompressed image that approximately occurs in the already processed image.
Proceedings ArticleDOI
Lossless image compression using generalized LZ1-type methods
TL;DR: This work generalizes "LZ1" type methods to lossless image compression to two dimensions with approximate matching and examines complexity issues and 2D implementations.
References
More filters
Journal ArticleDOI
Multidimensional binary search trees used for associative searching
TL;DR: The multidimensional binary search tree (or k-d tree) as a data structure for storage of information to be retrieved by associative searches is developed and it is shown to be quite efficient in its storage requirements.
Book
Vector Quantization and Signal Compression
Allen Gersho,Robert M. Gray +1 more
TL;DR: The author explains the design and implementation of the Levinson-Durbin Algorithm, which automates the very labor-intensive and therefore time-heavy and expensive process of designing and implementing a Quantizer.
Book
Computational Geometry: An Introduction
TL;DR: In this article, the authors present a coherent treatment of computational geometry in the plane, at the graduate textbook level, and point out the way to the solution of the more challenging problems in dimensions higher than two.
Journal ArticleDOI
An Algorithm for Finding Best Matches in Logarithmic Expected Time
TL;DR: An algorithm and data structure are presented for searching a file containing N records, each described by k real valued keys, for the m closest matches or nearest neighbors to a given query record.