From filters to features:Scale-space analysis of edge and blur coding in human vision

To make vision possible, the visual nervous system must represent the most informative features in the light pattern captured by the eye. Here we use Gaussian scale-space theory to derive a multiscale model for edge analysis and we test it in perceptual experiments. At all scales there are two stages of spatial filtering. An odd-symmetric, Gaussian first derivative filter provides the input to a Gaussian second derivative filter. Crucially, the output at each stage is half-wave rectified before feeding forward to the next. This creates nonlinear channels selectively responsive to one edge polarity while suppressing spurious or "phantom" edges. The two stages have properties analogous to simple and complex cells in the visual cortex. Edges are found as peaks in a scale-space response map that is the output of the second stage. The position and scale of the peak response identify the location and blur of the edge. The model predicts remarkably accurately our results on human perception of edge location and blur for a wide range of luminance profiles, including the surprising finding that blurred edges look sharper when their length is made shorter. The model enhances our understanding of early vision by integrating computational, physiological, and psychophysical approaches. © ARVO.

Third-derivative filters predict edge locations in spatial vision

Edge detection is crucial in visual processing. Previous computational and psychophysical models have often used peaks in the gradient or zero-crossings in the 2nd derivative to signal edges. We tested these approaches using a stimulus that has no such features. Its luminance profile was a triangle wave, blurred by a rectangular function. Subjects marked the position and polarity of perceived edges. For all blur widths tested, observers marked edges at or near 3rd derivative maxima, even though these were not 1st derivative maxima or 2nd derivative zero-crossings, at any scale. These results are predicted by a new nonlinear model based on 3rd derivative filtering. As a critical test, we added a ramp of variable slope to the blurred triangle-wave luminance profile. The ramp has no effect on the (linear) 2nd or higher derivatives, but the nonlinear model predicts a shift from seeing two edges to seeing one edge as the ramp gradient increases. Results of two experiments confirmed such a shift, thus supporting the new model. [Supported by the Engineering and Physical Sciences Research Council].

Mach edges: a key role for 3rd derivative filters in spatial vision

Edges are key points of information in visual scenes. One important class of models supposes that edges correspond to the steepest parts of the luminance profile, implying that they can be found as peaks and troughs in the response of a gradient (first-derivative) filter, or as zero-crossings (ZCs) in the second-derivative. A variety of multi-scale models are based on this idea. We tested this approach by devising a stimulus that has no local peaks of gradient and no ZCs, at any scale. Our stimulus profile is analogous to the classic Mach-band stimulus, but it is the local luminance gradient (not the absolute luminance) that increases as a linear ramp between two plateaux. The luminance profile is a smoothed triangle wave and is obtained by integrating the gradient profile. Subjects used a cursor to mark the position and polarity of perceived edges. For all the ramp-widths tested, observers marked edges at or close to the corner points in the gradient profile, even though these were not gradient maxima. These new Mach edges correspond to peaks and troughs in the third-derivative. They are analogous to Mach bands - light and dark bars are seen where there are no luminance peaks but there are peaks in the second derivative. Here, peaks in the third derivative were seen as light-to-dark edges, troughs as dark-to-light edges. Thus Mach edges are inconsistent with many standard edge detectors, but are nicely predicted by a new model that uses a (nonlinear) third-derivative operator to find edge points.

Surface acoustic wave devices with low loss and high frequency operation

This thesis describes an industrial research project carried out in collaboration with STC Components, Harlow, Essex. Technical and market trends in the use of surface acoustic wave (SAW) devices are reviewed. As a result, three areas not previously addressed by STC were identified: lower insertion loss designs, higher operating frequencies and improved temperature dependent stability. A review of the temperature performance of alternative lower insertion loss designs,shows that greater use could be made of the on-site quartz growing plant. Data is presented for quartz cuts in the ST-AT range. This data is used to modify the temperature performance of a SAW filter. Several recently identified quartz orientations have been tested. These are SST, LST and X33. Problems associated with each cut are described and devices demonstrated. LST quartz, although sensitive to accuracy of cut, is shown to have an improved temperature coefficient over the normal ST orientation. Results show that its use is restricted due to insertion loss variations with temperature. Effects associated with split-finger transducers on LST-quartz are described. Two low-loss options are studied, coupled resonator filters for very narrow bandwidth applications and single phase unidirectional transducers (SPUDT) for fractional bandwidths up to about 1%. Both designs can be implemented with one quarter wavelength transducer geometries at operating frequencies up to 1GHz. The SPUDT design utilised an existing impulse response model to provide analysis of ladder or rung transducers. A coupled resonator filter at 400MHz is demonstrated with a matched insertion loss of less than 3.5dB and bandwidth of 0.05%. A SPUDT device is designed as a re-timing filter for timing extraction in a long haul PCM transmission system. Filters operating at 565MHz are demonstrated with insertion losses of less than 6dB. This basic SPUDT design is extended to a maximally distributed version and demonstrated at 450MHz with 9.8dB insertion loss.