Adrian N. Evans

A morphological gradient approach to color edge detection

A new color edge detector based on vector differences is proposed. The basic technique gives as its output the maximum distance between the vectors within a mask. When applied to scalar-valued images, the method reduces to the classic morphological gradient. The technique is relatively computationally efficient and can also be readily applied to other vector-valued images. To improve the performance in the presence of noise, a novel pairwise outlier rejection scheme is employed. A quantitative evaluation using Pratts figure of merit shows the new technique to outperform other recently proposed color edge detectors. In addition, application to real images demonstrates the approach to be highly effective despite its low complexity.

Biased motion-adaptive temporal filtering for speckle reduction in echocardiography

Describes a new fully motion-adaptive spatio-temporal filtering technique to reduce the speckle in ultrasound images. The advantages of this approach are demonstrated in echocardiographic boundary detection and in comparison with other techniques. The first stage of many automated echocardiographic image interpretation schemes is filtering to reduce the amount of speckle noise. The authors show how the two-dimensional least mean squares (TDLMS) filter can be configured as a motion-compensated filter for a time sequence of ultrasound images that eliminates the blurring associated with direct averaging. For an image corrupted by multiplicative speckle noise, the mode of the intensity distribution approximates the maximum likelihood estimator. In consequence, the temporal filters output is biased towards the mode from the mean, using information contained within the speckle itself. A new adaptive algorithm for controlling the filters convergence is also included. To evaluate performance, application to simulated, phantom, and an in vivo test sequence of the carotid artery are considered in comparison with other techniques. The effect of filtering on edges is of great importance, as these are used by subsequent image interpretation schemes. Quantitative measurements demonstrate the effectiveness of the Biased TDLMS filter, for both noise reduction and edge preservation. Echocardiographic images have a high noise content and suffer from poor contrast. Despite this challenging environment, the Biased TDLMS filter is shown to produce images that are better inputs for subsequent feature extraction. The benefits for echocardiographic images are highlighted by considering the problems of mitral valve analysis and extraction of the left atrium boundary.

Relational matching by discrete relaxation

Abstract This paper describes a symbolic approach to relational matching. The novelty of the method lies in its Bayesian modelling of relational consistency which leads to a global matching criterion with a unique mathematical structure and robustness to error. Unlike many alternatives in the literature, the method is not limited to the use of binary constraints; it can accommodate N -ary relations of varying order. In consequence of this assumed model, the consistency of match is gauged by a compound exponential function of a higher-order Hamming distance between symbolic relations; there is a single exponential associated with each potential relational mapping. These exponential functions naturally soften the symbolic constraints represented by the relational mappings. This compound exponential structure also bestows a number of tangible benefits over the use of quadratic alternatives. In the first instance, it both renders the method more robust to errors and allows it to operate effectively in a large space of relational mappings. Moreover, this robustness to inconsistency means that the method may be operated without the need for an explicit null matching process. Unmatchable entities are identified by a constraint filtering operation once the relaxation scheme has converged. The utility of the method is illustrated on the matching of hedge structures in SAR images against their cartographic representation in a digital map.

Glacier surface motion computation from digital image sequences

A technique for computing the field of short-term glacier surface motion on a local scale is presented. Time-lapsed image negatives, digitized to a high resolution, provide the raw data for the three-stage technique. First, cross-correlation is used to establish a number of candidate displacement vectors for a series of regularly spaced templates. A relaxation-labeling routine is then applied to select the most appropriate candidate vectors, according to the local flow. Novel aspects of the relaxation algorithm include a new, efficient form of the support function and the absence of a null-match category. A new development is the application of a post filter to the resultant flow field, providing suitable displacement vectors for templates that were originally unmatched and correcting vectors that are still inconsistent with the local flow. Results from an image sequence from New Zealands Mount Cook National Park show the superiority of the technique over the maximum cross-correlation method and demonstrate the effectiveness of the post filter in improving correlation-relaxation labeling.

An Evaluation of Interpolation Techniques for Reconstructing Ionospheric TEC Maps

Maps of the total electron content (TEC) of the ionosphere can be reconstructed using data extracted from global positioning system (GPS) signals. For historic and other sparse data sets, the reconstruction of TEC images is often performed using a multivariate interpolation technique. Although there are many interpolation methods available, only a limited number, for example kriging, have been applied to TEC data. This paper presents a quantitative comparison of various commonly used algorithms for scattered-data interpolation over a range of sparsi- ties. Techniques evaluated include a relatively new approach called Adaptive Normalized Convolution (ANC) that has not previously been applied to ionospheric reconstruction. The proposed evaluation scheme employs a quantitative methodology applied to both simulated and real TEC data. Results show that, although the performance of kriging is good in many cases, it is several times worse than the best performing techniques at some sparsities. Natural-neighbor interpolation has a better overall performance than kriging for both simulated and TEC data. Although its performance is a few percent worse than other methods for the simulated data, ANC produces the best performance for the TEC reconstructions.

Cloud motion analysis using multichannel correlation-relaxation labeling

Cloud motion vectors derived from sequences of remotely sensed data are widely used by numerical weather prediction models and other meteorological and climatic applications. One approach to computing cloud motion vectors is the correlation-relaxation labeling technique, in which a set of candidate vectors for each template is refined using relaxation labeling to provide a local smoothness constraint. In this letter, an extension of the correlation-relaxation labeling framework to tracking clouds in multichannel imagery is presented. As this multichannel approach takes advantage of the diversity between channels, it has the potential for producing motion vectors with a superior quality and coverage than can be achieved by any individual channel. Results for visible and infrared images from Meteostat Second Generation confirm the benefits of the multichannel approach

An evaluation of area morphology scale-spaces for colour images

Area morphological scale-spaces are widely used for hierarchical image analysis and segmentation. Despite their advantages, their extension to colour images has been restricted by the lack of an explicit order relationship for vector values. This paper presents a theoretical evaluation of two recently proposed colour sieves and their properties. It is also demonstrated that the extrema definition used by a colour sieve determines both the aggressiveness of its sieving action and its processing speed. A new colour sieve structure is introduced that attempts to capture the relative advantages of the two sieves previously studied. An objective study of the noise reduction performance of these colour sieves is presented. The segmentation performance is also analysed using the methodology provided by the Berkeley Segmentation Dataset and Benchmark, both in terms of the overall segmentation performance and its robustness to image noise. The new colour sieve is shown to have the best overall segmentation performance, and to be the most robust.

A sequential vector selection algorithm for controllable bandwidth motion description encoding

The paper presents a method for controlling the bandwidth given to the motion description in motion-compensated video coding by restricting the number of motion vectors used. A new algorithm, called the metric method, for selecting the vectors is presented. This approach produces predicted images that are a close approximation of the optimal that can be achieved for a fixed number of vectors with relatively little additional computational cost. Results show that, in a video codec, the metric method produces lower overall errors than the standard approach of sending one vector per block, and is better than the histogram method previously used to select the vectors.

Map of low-frequency electromagnetic noise in the sky

The Earths natural electromagnetic environment is disturbed by anthropogenic electromagnetic noise. Here we report the first results from an electromagnetic noise survey of the sky. The locations of electromagnetic noise sources are mapped on the hemisphere above a distributed array of wideband receivers that operate in a small aperture configuration. It is found that the noise sources can be localized at elevation angles up to ∼60° in the sky, well above the horizon. The sky also exhibits zones with little or no noise that are found toward the local zenith and the southwest of the array. These results are obtained by a rigorous analysis of the residuals from the classic dispersion relation for electromagnetic waves using an array analysis of electric field measurements in the frequency range from ∼20 to 250 kHz. The observed locations of the noise sources enable detailed observations of ionospheric modification, for example, caused by particle precipitation and lightning discharges, while the observed exclusion zones enable the detection of weak natural electromagnetic emissions, for example, from streamers in transient luminous events above thunderclouds.

Array analysis of electromagnetic radiation from radio transmitters for submarine communication

The array analyses used for seismic and infrasound research are adapted and applied here to the electromagnetic radiation from radio transmitters for submarine communication. It is found that the array analysis enables a determination of the slowness and the arrival azimuth of the wave number vectors associated with the electromagnetic radiation. The array analysis is applied to measurements of ∼20–24 kHz radio waves from transmitters for submarine communication with an array of 10 radio receivers distributed over an area of ∼1 km ×1 km. The observed slowness of the observed wave number vectors range from ∼2.7 ns/m to ∼4.1 ns/m, and the deviations between the expected arrival azimuths and the observed arrival azimuths range from ∼−9.7° to ∼14.5°. The experimental results suggest that it is possible to determine the locations of radio sources from transient luminous events above thunderclouds with an array of radio receivers toward detailed investigations of the electromagnetic radiation from sprites.