An image compression/decompression method is proposed, based on a new interpolation formula of Hermite-Birkhoff type. It is based on a function representation that uses a truncated multipoint Taylor (MT) series. Given...
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An image compression/decompression method is proposed, based on a new interpolation formula of Hermite-Birkhoff type. It is based on a function representation that uses a truncated multipoint Taylor (MT) series. Given a regularly tabulated image, first spatial derivatives (up to a chosen order) are computed by a FFT algorithm. Secondly a knot placing strategy selects sample point positions. The image values and spatial derivatives at these sample points are stored as the compressed data. Decompression is achieved by applying the MT interpolant to the compressed data. The quality of compression is user controlled by specifying the maximum order of spatial derivatives and the number of knots to be used. The method is found to be superior to JPEG in both reduction factor and quality, when reasonable smooth data is to be compressed with high accuracy. In this case, data reduction ratios in the range 10-100 can be obtained with a root mean square reconstruction error of the order of 1-2%. For compression of real-life color images it is inferior to JPEG and yields reduction ratios of about 4, at the threshold of notable picture degradation to the eye. A number of compression/decompression examples are shown.
We briefly describe advancements in two broad areas of morphological image analysis. Part I deals with differential morphology and curve evolution. The partial differential equations (PDEs) that model basic morphologi...
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We briefly describe advancements in two broad areas of morphological image analysis. Part I deals with differential morphology and curve evolution. The partial differential equations (PDEs) that model basic morphological operations are first presented. The resulting dilation PDE, numerically implemented by curve evolution algorithms, improves the accuracy of morphological multiscale analysis by Euclidean disks and (its anisotropic/heterogeneous version) is the basic ingredient of PDE models that solve image analysis problems such as gridless halftoning and watershed segmentation based on the eikonal PDE. Part II deals with morphology-related systems for pattern recognition. It presents a general class of multilayer feedforward neural networks where the combination of inputs in every node is formed by hybrid linear and nonlinear (of the morphological/rank type) operations. For its design a methodology is formulated using ideas from the backpropagation algorithm and robust techniques are developed to circumvent the non-differentiability of rank functions. Experimental results in handwritten character recognition are described and illustrate some of the properties of this new type of neural nets.
The proceedings contains 29 papers from the X braziliansymposium of computer Graphic and imageprocessing. Topics discussed include: high quality rendering of two-dimensional continuous curves;real time rendering of ...
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The proceedings contains 29 papers from the X braziliansymposium of computer Graphic and imageprocessing. Topics discussed include: high quality rendering of two-dimensional continuous curves;real time rendering of photo-textured terrain height fields;interactive animation;hierarchical skeleton-based implicit model;representation of conics in the oriented projective plane;wavelet and entropy analysis combination to evaluate diffusion and correlation behaviors;multiscale segmentation and enhancement in mammograms;similarity-based versus template matching-based methodologies for image alignment of polyhedral-like objects under noisy conditions;and morphological operators characterized by neighborhood graphs.
This paper presents a methodology to morphological video segmentation used as part of a method to estimate the subjective video quality assessment. The segmentation goal is to partition the sequence frames in three di...
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This paper presents a methodology to morphological video segmentation used as part of a method to estimate the subjective video quality assessment. The segmentation goal is to partition the sequence frames in three different regions: homogeneous, border and texture. Previous work has shown the importance of computing video impairment measurements to each of these regions separately, in contrast to use global measurements. The segmentation approach presented in this work uses a collection of morphological tools such as connected smoothing filters, morphological gradients, and watershed. Special attention is devoted to describe the recent concept of connected filters, used as the kernel of the morphological segmentation algorithms. The performance of two morphological segmentation paradigms, one based on the flat zone, and the other based on the watershed-plus-markers approach are evaluated and compared to other segmentation methodology used in video quality assessment.
In the advent of the ubiquity of distributed computing with multimedia capabilities, it is very natural to contemplate collaborations that were not previously possible. In the past scientists, doctors, educators, engi...
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In the advent of the ubiquity of distributed computing with multimedia capabilities, it is very natural to contemplate collaborations that were not previously possible. In the past scientists, doctors, educators, engineers always had need to share, exchange, debate their work, designs, methodology, knowledge and experience. This was commonly done by attending meetings, publishing in common journals, sometimes books, and visiting each other's laboratories, research institutions, or attending lectures at universities. Recently, advances in computer vision, computergraphics and networking, make possible a new way of communication by immersing participants at remote sites into a common 3D virtual world. The 3D virtual world is high quality, realistic, dynamically updated representation which joins the models of the real worlds at each of the remote sites. This virtual world provides means for telecollaboration, it makes the real-time 3D interaction of people at remote locations possible. We describe the new "teleimmersion" technology. We concentrate on the current state of our research related to the problem of accurate, precise, real-time recovery of the individual remote 3D models, their merging into a common virtual world, and the real-time rendering of this world.
We describe an efficient parallel algorithm for hidden-surface removal for terrain maps. The algorithm runs in O(log/sup 4/ n) steps on the CREW PRAM model with a work bound of O((n+k)polylog(n)) where n and k are the...
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We describe an efficient parallel algorithm for hidden-surface removal for terrain maps. The algorithm runs in O(log/sup 4/ n) steps on the CREW PRAM model with a work bound of O((n+k)polylog(n)) where n and k are the input and output sizes respectively. In order to achieve the work bound we use a number of techniques, among which our use of persistent data-structures is somewhat novel in the context of parallel algorithms. To the best of our knowledge this is the most efficient parallel algorithm for hidden-surface removal for an important class of 3-D scenes.
Rendering high-quality computer animations requires intensive computation, and therefore a large amount of time. One way to speed up this process is to devise rendering algorithms which reduce computation by taking ad...
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Rendering high-quality computer animations requires intensive computation, and therefore a large amount of time. One way to speed up this process is to devise rendering algorithms which reduce computation by taking advantage of image characteristics, such as frame or temporal coherence. Another way is to run the rendering process on specialized or enhanced hardware, such as a multiprocessor machine. This paper details our experiences in combining these techniques through a parallel rendering algorithm exploiting frame coherence run on a network of workstations acting as a single processing system. This system provides a powerful and general method for obtaining high-quality animations with a significant reduction in computation and overall processing time. We present several techniques for partitioning the data across the workstation processors and report our results for each. While all of the partitioning schemes are scalable, some handle load balancing more effectively than others.
A VLSI architecture designed to perform real-time image compression using wavelets is described. The two basic modules of the architecture are a 2-D wavelet transform generator and a coder based on the SPIHT algorithm...
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A VLSI architecture designed to perform real-time image compression using wavelets is described. The two basic modules of the architecture are a 2-D wavelet transform generator and a coder based on the SPIHT algorithm for lossy image compression. A folded architecture is proposed for computing the 2-D wavelet transform. The architecture uses 3 parallel computational units and 2 storage units. The hardware for the SPIHT coder uses 2 content addressable memories and 3 random access memories. The designs are modular and can easily be extended for different levels of wavelet decomposition and filter lengths. The derived architecture has been functionally verified for an 8/spl times/8 image size by simulating its VHDL code using Mentor graphics.
The Algebraic Reconstruction Technique (ART) reconstructs a 2D or 3D object from its projections. It has, in certain scenarios, many advantages over the more popular Filtered Backprojection approaches and has also rec...
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The Algebraic Reconstruction Technique (ART) reconstructs a 2D or 3D object from its projections. It has, in certain scenarios, many advantages over the more popular Filtered Backprojection approaches and has also recently been shown to perform well for 3D cone-beam reconstruction. However, so far ART's slow speed has prohibited its routine use in clinical applications. Here, the authors devise a new hardware acceleration scheme, employing readily available texture mapping graphics hardware, that allows quality 3D cone-beam reconstructions to be obtained at almost interactive speeds.
This paper presents the implementation of a coprocessor that speeds up Roberts gradient edge detection on monochromatic images with 256 gray levels. The coprocessor is implemented in a reconfigurable computing system ...
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This paper presents the implementation of a coprocessor that speeds up Roberts gradient edge detection on monochromatic images with 256 gray levels. The coprocessor is implemented in a reconfigurable computing system based on a board for PC-based platforms using off-the-shelf FPGAs.
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