✦ LIBER ✦

Image Compression Based on Multistage Vector Quantization

✍ Scribed by Chaur-Heh Hsieh; Wei-Yang Shao; Ming-Haw Jing

Publisher: Elsevier Science
Year: 2000
Tongue: English
Weight: 436 KB
Volume: 11
Category: Article
ISSN: 1047-3203
DOI: 10.1006/jvci.2000.0452

No coin nor oath required. For personal study only.

✦ Synopsis

This paper presents a new three-stage vector quantization system for the compression of images. It uses some simple schemes including error block classifier, search order coding (SOC), and index vector coding. The error block classifier preserves the edge blocks and discards the psychovisually redundant texture blocks in the last stage. The index vector coding encodes the combination of quantization indexes of the last two stages, and the SOC is used for encoding the quantization index of the first stage. The proposed system can achieve better compression performance than the conventional multistage vector quantization systems.

📜 SIMILAR VOLUMES

A new shape-vector quantization-based ad

A new shape-vector quantization-based adaptive predictive image coder

✍ Jian Wang; Golshah Naghdy 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 156 KB

In this paper, a new lossless image compression technique, shape-vector quantization (VQ)-based adaptive predictive coder (SAPC), is introduced. In the proposed scheme, the local shape information of the image block is obtained through shape-VQ. This information is utilized by a novel predictive cod

Image coding based on wavelet feature ve

Image coding based on wavelet feature vector

✍ Shinfeng D. Lin; Shih-Chieh Shie; Kuo-Yuan Lee 📂 Article 📅 2005 🏛 John Wiley and Sons 🌐 English ⚖ 129 KB

## Abstract In this article, an efficient image coding scheme that takes advantages of feature vector in wavelet domain is proposed. First, a multi‐stage discrete wavelet transform is applied on the image. Then, the wavelet feature vectors are extracted from the wavelet‐decomposed subimages by coll

Very-high-quality image compression base

Very-high-quality image compression based on noise modeling

✍ Fionn Murtagh; Jean-Luc Starck; Mireille Louys 📂 Article 📅 1998 🏛 John Wiley and Sons 🌐 English ⚖ 173 KB

We present a new image compression method for veryhave wide currency and have been the subject of comparisons high-quality lossy compression. This method caters for image data with the method described here (in the case of HCOMPRESS in in regimes of (a) detector imperfections, which motivates a robu

Adaptive image compression based on segm

Adaptive image compression based on segmentation and block classification

✍ Mahmoud R. El-Sakka; Mohamed S. Kamel 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 563 KB

This article presents a new digital image compression scheme which exploits a human visual system property-namely, recognizing images by their regions-to achieve high compression ratios. It also assigns a variable bit count to each image region that is proportional to the amount of information it co

EEG signal compression based on classifi

EEG signal compression based on classified signature and envelope vector sets

✍ Hakan Gürkan; Umit Guz; B. Siddik Yarman 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 544 KB

## Abstract In this paper, a novel method to compress electroencephalogram (EEG) signal is proposed. The proposed method is based on the generation process of the classified signature and envelope vector sets (CSEVS), which employs an effective __k__‐means clustering algorithm. It is assumed that b

Near-infrared Raman imaging microscope b

Near-infrared Raman imaging microscope based on fiber-bundle image compression

✍ Alan D. Gift; Jiaying Ma; Kenneth S. Haber; Brian L. McClain; Dor Ben-Amotz 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 285 KB

The design and performance of a near-infrared Raman imaging microscope (NIRIM) is described. This new instrument utilizes fiber-bundle image compression (FIC) to collect simultaneously a 3-D Raman spectral imaging data cube. Key NIRIM design features are discussed, including the FIC fiber-bundle, ex