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43
Determining Optical Flow
 ARTIFICIAL INTELLIGENCE
, 1981
"... Optical flow cannot be computed locally, since only one independent measurement is available from the image sequence at a point, while the flow velocity has two components. A second constraint is needed. A method for finding the optical flow pattern is presented which assumes that the apparent veloc ..."
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Cited by 1727 (7 self)
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Optical flow cannot be computed locally, since only one independent measurement is available from the image sequence at a point, while the flow velocity has two components. A second constraint is needed. A method for finding the optical flow pattern is presented which assumes that the apparent velocity of the brightness pattern varies smoothly almost everywhere in the image. An iterative implementation is shown which successfully computes the optical flow for a number of synthetic image sequences. The algorithm is robust in that it can handle image sequences that are quantized rather coarsely in space and time. It is also insensitive to quantization of brightness levels and additive noise. Examples are included where the assumption of smoothness is violated at singular points or along lines in the image.
Linear and Cubic Box Splines for the Body Centered Cubic Lattice
 In Proceedings of the IEEE Conference on Visualization
, 2004
"... In this paper we derive piecewise linear and piecewise cubic box spline reconstruction filters for data sampled on the body centered cubic (BCC) lattice. We analytically derive a time domain representation of these reconstruction filters and using the Fourier sliceprojection theorem we derive their ..."
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Cited by 31 (6 self)
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In this paper we derive piecewise linear and piecewise cubic box spline reconstruction filters for data sampled on the body centered cubic (BCC) lattice. We analytically derive a time domain representation of these reconstruction filters and using the Fourier sliceprojection theorem we derive their frequency responses. The quality of these filters, when used in reconstructing BCC sampled volumetric data, is discussed and is demonstrated with a raycaster. Moreover, to demonstrate the superiority of the BCC sampling, the resulting reconstructions are compared with those produced from similar filters applied to data sampled on the Cartesian lattice.
SPATIOSPECTRAL COLOR FILTER ARRAY DESIGN FOR ENHANCED IMAGE FIDELITY
"... In digital imaging applications, data are typically obtained via a spatial subsampling procedure implemented as a color filter array—a physical construction whereby only a single color representative is measured at each pixel location. Owing to the growing ubiquity of color imaging and display devic ..."
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Cited by 21 (4 self)
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In digital imaging applications, data are typically obtained via a spatial subsampling procedure implemented as a color filter array—a physical construction whereby only a single color representative is measured at each pixel location. Owing to the growing ubiquity of color imaging and display devices, much recent work has focused on the interplay between color filter array design and subsequent digital processing, including in particular the canonical spatiochromatic reconstruction task known as demosaicking. Here we consider the problem of improved color filter array design, leading to enhanced image fidelity. We first analyze the limitations of the wellknown Bayer pattern, currently most popular in industry. We then propose a framework for designing rectangular color filter arrays amenable to efficient and completely linear reconstruction, and provide examples of new patterns that enable improvements in reconstruction quality. Index Terms — Image sensors, color measurement, image sampling, image reconstruction, image color analysis 1.
Practical box splines for reconstruction on the body centered cubic lattice
 IEEE Trans. Vis. Comput. Graphics
, 2008
"... Abstract—We introduce a family of box splines for efficient, accurate, and smooth reconstruction of volumetric data sampled on the bodycentered cubic (BCC) lattice, which is the favorable volumetric sampling pattern due to its optimal spectral sphere packing property. First, we construct a box spli ..."
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Cited by 19 (2 self)
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Abstract—We introduce a family of box splines for efficient, accurate, and smooth reconstruction of volumetric data sampled on the bodycentered cubic (BCC) lattice, which is the favorable volumetric sampling pattern due to its optimal spectral sphere packing property. First, we construct a box spline based on the four principal directions of the BCC lattice that allows for a linear C 0 reconstruction. Then, the design is extended for higher degrees of continuity. We derive the explicit piecewise polynomial representations of the C 0 and C 2 box splines that are useful for practical reconstruction applications. We further demonstrate that approximation in the shiftinvariant space—generated by BCClattice shifts of these box splines—is twice as efficient as using the tensorproduct Bspline solutions on the Cartesian lattice (with comparable smoothness and approximation order and with the same sampling density). Practical evidence is provided demonstrating that the BCC lattice not only is generally a more accurate sampling pattern, but also allows for extremely efficient reconstructions that outperform tensorproduct Cartesian reconstructions. Index Terms—BCC, box splines, discrete/continuous representations, optimal regular sampling. Ç 1
Image Resampling
, 1992
"... This dissertation considers several aspects of the process ..."
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Cited by 15 (3 self)
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This dissertation considers several aspects of the process
A Comparison Between Square and Hexagonal Sampling Methods for Pipeline Image Processing
, 1989
"... The majority of machine vision systems derive their input data by digitising an image to produce a square grid of sampled points. However, other sampling techniques can represent equal picture information in a smaller number of samples, with a consequent reduction in data rate. Several workers have ..."
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Cited by 10 (0 self)
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The majority of machine vision systems derive their input data by digitising an image to produce a square grid of sampled points. However, other sampling techniques can represent equal picture information in a smaller number of samples, with a consequent reduction in data rate. Several workers have looked at regular hexagonal sampling of images which produces optimum data rates for a given information content. Previous work on hexagonal sampling by the authors and others, has shown that image processing operators are computationally more efficient, and as accurate, as their square counterparts. Historically, one factor which has lead to the predominance of square sampling in vision systems, is that this produces images which are more visually pleasing to human observers. This paper describes an investigation of machine vision systems performing industrial inspection tasks, which suggests that in such applications, hexagonal systems outperform square systems. In particular hexagonal op...
Segmentation of Color Images Using a TwoStage SelfOrganizing Network
 Image and Vision Computing
, 2002
"... We propose a twostage hierarchical artificial neural network for the segmentation of color images based on the Kohonen selforganizing map (SAM). The first stage of the network employs a fixedsize twodimensional feature map that captures the dominant colors of an image in an unsupervised mode. Th ..."
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Cited by 10 (1 self)
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We propose a twostage hierarchical artificial neural network for the segmentation of color images based on the Kohonen selforganizing map (SAM). The first stage of the network employs a fixedsize twodimensional feature map that captures the dominant colors of an image in an unsupervised mode. The second stage combines a variablesized onedimensional feature map and color merging to control the number of color clusters that is used for segmentation. A postprocessing noisefiltering stage is applied to improve segmentation quality. Experiments confirm that the selflearning ability, fault tolerance and adaptability of the twostage SaM lead to a good segmentation results. 2002 Elsevier Science B.V. All rights reserved.
Hexagonal Structure for Intelligent Vision
, 2005
"... Using hexagonal grids to represent digital images have been studied for more than 40 years. Increased processing capabilities ofgraphic devices and recent improvements in CCD technology have made hexagonal sampling attractive for practical applications and brought new interests on this topic. The he ..."
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Cited by 9 (1 self)
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Using hexagonal grids to represent digital images have been studied for more than 40 years. Increased processing capabilities ofgraphic devices and recent improvements in CCD technology have made hexagonal sampling attractive for practical applications and brought new interests on this topic. The hexagonal structure is considered to be preferable to the rectangular structure due to its higher sampling efficiency, consistent connectivity and higher angular resolution and is even proved to be superior to square structure in many applications. Since there is no mature hardware for hexagonalbased image capture and display, square to hexagonal image conversion has to be done before hexagonalbased image processing. Although hexagonal image representation and storage has not yet come to a standard, experiments based on existing hexagonal coordinate systems have never ceased. In this paper, we firstly introduced general reasons that hexagonally sampled images are chosen for research. Then, typical hexagonal coordinates and addressing schemes, as well as hexagonal based image processing and applications, are fully reviewed.
Generalized Bremmer series with rational approximation for the scattering of waves in . . .
, 1998
"... ..."
Characterization of Visually Similar Diffuse Diseases from BScan Liver Images Using Nonseparable Wavelet Transform
 Proc. 1997 IEEE Int. Conf. Image Processing
, 1997
"... This paper describes a new approach for texture characterization, based on nonseparable wavelet decomposition, and its application for the discrimination of visually similar diffuse diseases of liver. The proposed featureextraction algorithm applies nonseparable quincunx wavelet transform and uses ..."
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Cited by 8 (1 self)
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This paper describes a new approach for texture characterization, based on nonseparable wavelet decomposition, and its application for the discrimination of visually similar diffuse diseases of liver. The proposed featureextraction algorithm applies nonseparable quincunx wavelet transform and uses energies of the transformed regions to characterize textures. Classification experiments on a set of three different tissue types show that the scale/frequency approach, particularly one based on the nonseparable wavelet transform, could be a reliable method for a texture characterization and analysis of Bscan liver images. Comparison between the quincunx and the traditional wavelet decomposition suggests that the quincunx transform is more appropriate for characterization of noisy data, and practical applications, requiring description with lower rotational sensitivity.