Ronald B. Arps

An overview of the basic principles of the Q-Coder adaptive binary arithmetic coder

The Q-Coder is a new form of adaptive binary arithmetic coding. The binary arithmetic coding part of the technique is derived from the basic concepts introduced by Rissanen, Pasco, and Langdon, but extends the coding conventions to resolve a conflict between optimal software and hardware implementations. In addition, a robust form of probability estimation is used in which the probability estimate is derived solely from the interval renormalizations that are part of the arithmetic coding process. A brief tutorial of arithmetic coding concepts is presented, followed by a discussion of the compatible optimal hardware and software coding structures and the estimation of symbol probabilities from interval renormalization.

Technical features of the JBIG standard for progressive bi-level image compression

Abstract The JBIG coding standard like the G3 and G4 facsimile standards defines a method for the lossless (bit-preserving) compression of bi-level (two-tone or black/white) images. One advantage it has over G3/G4 is superior compression, especially on bi-level images rendering greyscale via halftoning. On such images compression improvements as large as a factor of ten are common. A second advantage of the JBIG standard is that it can be parameterized for progressive coding. Progressive coding has application in image databases that must serve displays of differing resolution, image databases delivering images to CRT displays over medium rate (say, 9.6 to 64 kbit/s) channels, and image transmission services using packet networks having packet priority classes. It is also possible to parameterize for sequential coding in applications not benefiting from progressive buildup. It is possible to effectively use the JBIG coding standard for coding greyscale and color images as well as bi-level images. The simple strategy of treating bit-planes as independent bi-level images for JBIG coding yields compressions at least comparable to and sometimes better than the JPEG standard in its lossless mode. The excellent compression and great flexibility of JBIG coding make it attractive in a wide variety of environments.

Infornation Content Analysis of Landsat Image Data for Compression

This paper investigates information-preserving compressionof Landsat image data based on an entropy study. Measurementsof the statistical information in actual Landsat-4 images indicate a 3 : 1compression ratio can be achieved with a simple real-time compressionscheme.

Character Legibility versus Resolution in Image Processing of Printed Matter

In order to determine optimum resolution requirements for digital facsimile systems, a legibility study was conducted. The study was designed to measure the quality of output copy as a function of equipment parameters and copy parameters. The experimental equipment permitted systematic variations in horizontal and vertical resolution, scan direction, and simulated transmission noise; the test documents prepared included uppercase and lowercase characters of several sizes. During the course of the overall study, more than 300 subjects read the facsimile output copies; approximately 750 000 responses were accumulated and analyzed. The data are summarized by showing the spatial resolutions required to maintain 97.5 percent legibility for varying character sizes. Measurements were also made on secondary parameters, indicating slight differences in legibility due to scan direction, and a decrease in legibility when type was lowercase rather than uppercase. The decrease in legibility was also measured for a model of channel errors that assumes the use of run-length compression coding. Some of the results of this study can be generalized to other display systems.

PRECIS: A method for fast compression of periodic halftones

Summary form only given. The Periodic Run Edge Compression for Image Systems (PRECIS) is a simple, fast algorithm to compress bitonal images containing periodic halftones. Its compression of periodic halftones doubles and often quadruples the compression obtained using the commonly used MMR algorithm. Its software execution time in compressing periodic halftones has been measured to be as short as half the execution time of MMR. In addition, one software embodiment of a simple version of PRECIS can be implemented simply by clever reuse of building blocks from an existing MMR implementation.