We present extensions to an approach for rendering time-varying data based on the shear-warp factorisation. The change detection technique is adapted to process Poisson distributed datasets, a modified block differencing technique that decreases the change detection errors is presented along with a modification of the original run-length encoding method which allows better spatial compression for volume with uniform and slowly changing background. Results are presented on datasets originating from optical microscopes which demonstrate the efficiency of the proposed methods.

We introduce a novel formulation of the Circle Hough Transform that we call the Coherent Circle Hough Transform. The technique uses phase to code for radii of circles. The usual simplifications of the Circle Hough Transform (CHT) are used in which lines pointing away from edge points are plotted rather than circles. Intersections of these "spokes " accumulate edge magnitude, or edge "energy", near the centres of circles. We introduce the use of a complex accumulator space and allow each spoke to vary in phase along its length. The spokes are in phase near the centre of circles and out of phase elsewhere. The spokes generated by noise are in random phase and destructively interfere. We present results for an isolated circle with additive white Gaussian noise for both the conventional Energy CHT and the new Coherent CHT. The results demonstrate that the technique reduces the mean and variance of the background level in the accumulator array, that the peak to background level improves, and that the peak width is reduced improving localisation of circle centres.

The measurement of multiple velocities using phase-based methods is discussed. In particular, phase gradients (instantaneous frequency) from different bandpass channels (quadrature filter outputs) are used to estimate multiple image velocities in a single neighborhood. The approach is similar to that of M. Shizawa and K. Mase (1990) in which nth-order differential operators are required to compute n simultaneous velocity estimates. However, to use instantaneous frequency, the output of each channel must be differentiated only once.>

The use of a heterogeneous multiple-SIMD (M-SIMD) architecture with image-based measurements and optimal (Kalman) estimators for the analysis of image sequences is illustrated. The architecture integrates SIMD and MIMD processing paradigms, combining heterogeneity of processor types matched to the computation at each level and operational autonomy within an SIMD array. It is suited to real-time simultaneous data parallel (iconic) and control parallel (numeric) processing.>

The application of multiple-single instruction multiple-data (M-SIMD) processing techniques to the problem of finding straight lines in an image is described, and the advantages of using these techniques instead of direct SIMD computation are illustrated by reference to a hierarchical architecture: the Warwick pyramid machine. The advantages over conventional implementations of the Hough transform are discussed, and performance timings for a hierarchical implementation are provided.>

The Warwick Pyramid Machine, an architecture consisting of both SIMD and MIMD parts in a multiple SIMD organization which can operate effectively at all levels of an image analysis problem, is described. The hardware design is discussed, along with programming issues. Several image analysis algorithms that have been mapped onto the architecture are presented.>

The navigation and guidance of a mobile robot depend on inferences made from sensor measurements. Acoustic rangers offer the prospect of a simple means of determining range and direction but cannot in general be relied upon to measure the true range. To overcome this problem acoustic cats' eyes (the acoustical analog of optical retroreflectors found on highways) were attached to the smooth vertical surfaces in the laboratory. A standard Polaroid sonar ranger was rotated through one complete circle while range measurements were taken at regular intervals. This experiment was repeated without these devices. The range readings were then superimposed onto an architect's plan view of the area. The range scans taken with the acoustic cats' eyes show a significantly higher degree of correspondence to the plan view than do the range scans taken without them. It is shown that by identifying step changes in the derivative (the curvature) with respect to direction a decision space is created from which the presence and location of corners, walls, and doorways can be inferred.>