RAVI (representation for audio/visual interactive applications), a set of specifications proposed as a standard for the interchange of audio/visual interactive applications (AVIs), is presented. RAVI was designed to meet the functional requirements of an AVI. RAVI consists of an interchange format and a set of functional operators (formulation). Protocols for a RAVI system are defined to allow communication between distributed subsystems. RAVI profiles allow compatible implementation of restricted sets of functionalities. As far as possible, the RAVI specifications use existing standards and are being submitted to ISO and CCITT for discussion. Products are commercially available, and a number of applications has already been developed.>

In this paper, an algorithm is presented for extracting edges and estimating their local characteristics in TV pictures; the algorithm is designed for application to adaptive DPCM coding of TV pictures and it has the following properties: 1) it takes into account the causality constraint encountered in DPCM coding; 2) it is fitted to the line-by-line scanning of TV pictures; 3) it is fast, involving only a small amount of computation, and thus allowing real-time implementation. The whole processing is split into a local preprocessing and a global processing where the characteristics of the edges are renewed recursively line by line. This algorithm was used for implementing an adaptive choice of the prediction in DPCM coding of TV pictures.

The present study is devoted to the statistical analysis of edges in still monochrome TV pictures. The visual information carried by the edges is especially important both for image interpretation and for subjective image quality evaluation. Statistical knowledge on edges is helpful to improve image coding techniques significantly as well as processing techniques for scene analysis. After an introduction on nonstationary local statistical models, we describe the parameters of edges and the methods used to measure them. Statistical data collected on these parameters are then presented. The data concern orientation, edge length, edge width, runlength between edges and edge slope probability distributions as well as the measure of orientation continuity along an edge and the relative frequencies of edge pixels and contrasted isolated pixels.

The problem of quantization has been thoroughly studied for random processes. The usual criterion is to minimize the mean square error. Because of the eye's characteristics, this does not lead to the least number of bits. In this concise paper the results of experiments on gray scales and on quantized pictures are presented which lead to the choice of a compressor with a subjectively optimal parameter in the class of logarithmic compressors. Comparisons are made between the minimum mean square error quantizers on luminance signals, the usual quantizer for television signals (linear quantizer after a gamma correction) and the proposed quantization scheme designed for real visual scenes.