Finite context models improve the performance of chain based encoders to the point that they become attractive, alternative models for binary image compression. The resulting code is within 4% of JBIG at 200 dpi and is 9% more efficient at 400 dpi.

The design of a wavelet image coder can be divided into three parts: wavelet representation, quantization, and error-free encoding. We evaluate each of these parts individually and synthesize them into complete coders. The evaluation is in the rate-distortion sense; two image quality metrics are used: a perception-based, quantitative picture quality scale (PQS) and the conventional distortion measure, peak signal-to-noise ratio (PSNR). Two representative wavelets, three quantizers, three encoders, and some combinations of these parts are comparatively evaluated. Our results provide an insight into the design issues of optimizing wavelet coders, as well as a good reference for application developers to choose from an increasingly large family of wavelet coders for their applications.

In image processing operations involving changes in the sampling grid, including increases or decreases in resolution, care must be taken to preserve image structure. Structure includes regions of high contrast, such as edges, streaks, or corners, all indicated by large gradients. The authors consider the use of local spatial analysis for both sampling and interpolation. Anisotropic diffusion is considered as a directional smoothing technique that preserves structure. This is used in conjunction with a method of directional interpolation, which is also based on structure analysis.>

Some preliminary results are presented on a simple progressive code for scanned 300 dpi documents. The effectiveness of the standard CCITT codes as a function of document resolution is determined. Extensions to the technique of document resolution are examined. For higher-resolution scanning, e.g. 300 dpi, a pyramid of the information source which allows for a tradeoff between the compression achieved and the quality of the representation is proposed. A progressive code that first generates a color block image that may be useful for identification of the document is proposed. Progression in quality corresponds to 100 dpi binary images, 100 dpi gray scale images, 300 dpi binary images, and finally 300 dpi gray-scale images. Each stage in the progressive code is based on the data available at the previous stage. The performance of the progressive code is examined.>

Algorithms for preprocessing, global modeling and segmentation, local modeling and representation, and binary encoding of facsimile images are proposed, and their performance is examined. Some binary morphological operations that can be used to improve the quality and increase the compressibility of binary images and the modeling of binary images are discussed. The techniques are incorporated into a set of comprehensive encoding schemes, the PCSE codes. Their effectiveness in compressing the International Telegraphy and Telephony Consultative Committee (CCITT) binary images is demonstrated. The PCSE code using preprocessing and color shrinking prior to encoding is shown to outperform the READ code by from 7 to 42% for the standard CCITT test images with a very small change in image quality.>