JOURNAL ARTICLE

<title>Perceptually lossy compression of documents</title>

Giordano B. BerettaVasudev BhaskaranΚωνσταντίνος ΚωνσταντινίδηςBalas R. Natarajan

Year: 1997 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 3016 Pages: 126-133   Publisher: SPIE

Abstract

The main cost of owning a facsimile machine consists of the telephone charges for the communications, thus short transmission times are a key feature for facsimile machines. Similarly, on a packet-routed service such as the Internet, a low number of packets is essential to avoid operator wait times. Concomitantly, the user expectations have increased considerably. In facsimile, the switch from binary to full color increases the data size by a factor of 24. On the Internet, the switch from plain text American Standard Code for Information Interchange (ASCII) encoded files to files marked up in the Hypertext Markup Language (HTML) with ample embedded graphics has increased the size of transactions by several orders of magnitude. A common compressing method for raster files in these applications in the Joint Photographic Experts Group (JPEG) method, because efficient implementations are readily available. In this method the implementors design the discrete quantization tables (DQT) and the Huffman tables (HT) to maximize the compression factor while maintaining the introduced artifacts at the threshold of perceptual detectability. Unfortunately the achieved compression rates are unsatisfactory for applications such as color facsimile and World Wide Web (W3) browsing. We present a design methodology for image-independent DQTs that while producing perceptually lossy data, does not impair the reading performance of users. Combined with a text sharpening algorithm that compensates for scanning device limitations, the methodology presented in this paper allows us to achieve compression ratios near 1:100.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Keywords:
Computer science Facsimile Lossy compression Huffman coding ASCII File size Data compression JPEG The Internet Computer hardware Transmission (telecommunications) Artificial intelligence Telecommunications World Wide Web Operating system

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Topics

Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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