Adaptive vector quantization for lossy compression of image sequences
type: Item
instance of: scholarly article
title: Adaptive vector quantization for lossy compression of image sequences
zbMATH Open document ID: 1461.68245
author: Raffaele Pizzolante
author: Bruno Carpentieri
author: Sergio De Agostino
published in: Algorithms
publication date: 2018-08-20T00:00:00Z
review text: Summary: In this work, we present a scheme for the lossy compression of image sequences, based on the Adaptive Vector Quantization (AVQ) algorithm. The AVQ algorithm is a lossy compression algorithm for grayscale images, which processes the input data in a single-pass, by using the properties of the vector quantization to approximate data. First, we review the key aspects of the AVQ algorithm and, subsequently, we outline the basic concepts and the design choices behind the proposed scheme. Finally, we report the experimental results, which highlight an improvement in compression performances when our scheme is compared with the AVQ algorithm.
Mathematics Subject Classification ID: 68U10
Mathematics Subject Classification ID: 68P30
zbMATH DE Number: 6920637
zbMATH Keywords: lossy compression
zbMATH Keywords: adaptive vector quantization
zbMATH Keywords: image sequences
zbMATH Keywords: data compression
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.3390/a10020051
OpenAlex ID: W2612151195
cites work: Q4271995
cites work: Compression of individual sequences via variable-rate coding
cites work: Two-dimensional encoding by finite-state encoders
cites work: Scalability and communication in parallel low-complexity lossless compression
DOI: 10.3390/A10020051
description: scientific article; zbMATH DE number 6920637