Abstract-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 Pratt's 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.Index Terms-Color image processing, edge detection, morphological operations.

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 SecondGeneration confirm the benefits of the multichannel approach.

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 sparsities. 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. He has published over 50 papers in journals and refereed conference proceedings. His current research interests include nonlinear image processing, feature extraction and motion estimation in application to remotely sensed, color and multispectral images, and video compression.

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 Zealand's 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.

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