This paper proposes a 3-stage ATM switch architecture that uses optical WDM (wavelength division multiplexing) grouped links and dynamic bandwidth sharing. The proposed architecture has two features. The first is the use of WDM technology which makes the number of cables used in the system proportional to system size. The second is the use of dynamic bandwidth sharing among WDM grouped links. This prevents the statistical multiplexing gain offered by WDM from falling even if switching system becomes large. A performance evaluation confirms the scaleability and cost-effectiveness of the proposed architecture. It is scaleable in terms of the number of cables and admissible load. We show how the appropriate wavelength signal speed can be determined to implement the switch in a cost-effective manner. Therefore, the proposed architecture will suit future high-speed multimedia ATM networks.

This paper proposes a 3-stage ATM switch architecture that uses optical WDM (wavelength division multiplexing) grouped links and dynamic bandwidth sharing. The proposed architecture has two features. The first is the use of WDM technology which makes the number of cables used in the system proportional to system size. The second is the use of dynamic bandwidth sharing among WDM grouped links. This prevents the statistical multiplexing gain offered by WDM from falling even if switching system becomes large. A performance evaluation confirms the scaleability and cost-effectiveness of the proposed architecture. It is scaleable in terms of the number of cables and admissible load. We show how the appropriate wavelength signal speed can be determined to implement the switch in a cost-effective manner. Therefore, the proposed architecture will suit future high-speed multimedia ATM networks.

We propose a new method of progressive transmission of continuous tone images using multi-level error diffusion method. Assuming that the pixels are ordered and the error is diffused to later pixels, multi-level error-diffused images are resolved into a multiple number of bit planes. In an image with 8 bits per pixel, the number of the bit planes that we construct is 9, and the 2-level, 3-level, 5-level,, error-diffused images are produced by a successive use of the bit planes. The original image is finally achieved precisely.

In ATM Network, the VBR (Variable Bit Rate) service category is used to accommodate TCP/IP traffic. In an international ATM network with large propagation delay, higher TCP throughput can be obtained by use of window scale option. In order to accommodate TCP traffic with window scale option effectively, it is required to select appropriate values of VBR parameters, i. e. SCR (Sustainable Cell Rate) and MBS (Maximum Burst Size), and to evaluate the impact of UPC (Usage Parameter Control) function on TCP throughput. We have studied those technical issues for the conventional TCP, but the results cannot be applied to TCP traffic with the window scale option due to the TCP terminal performance and the large window size. In this paper, we proposed VBR parameter determination method for TCP with the window scale option and evaluated the values in each condition. These results show that the determined MBS is much smaller than the burst length of TCP segments especially using low performance TCP terminals. Furthermore, we also discuss some experimental results of TCP throughput degradation due to UPC function. It shows that the throughput of TCP with large window size is degraded when the SCR and MBS values used in ATM switch are smaller than the determined values.

The performance of AC plasma displays has been improved in the area of brightness and contrast, while significant advances in image quality are still required for the HDTV quality. In particular, in full color motion video, motion artifacts and lack of color depth are still visible in some situations. These motional artifacts are mitigated as the number of the subfields increases, usually at the cost of losing brightness or increasing driving circuitry. Therefore, it is still one of our great concerns to find out the optimized subfield configuration through weighting and order of each subfield, and their coding of combination. For evaluation and improvement of motion picture disturbance, we have established a procedure that fully simulates the image quality of displays which utilize the subfield driving scheme. The simulation features virtually located sensor pixels on human retina, eye-tracking sensor windows, and a built-in spatial low pass filter. The model pixelizes the observers retina like a sensor chip in a CCD camera. An eye-tracking sensor window is assigned to every light emission from the display, to calculate the emissions from one to four adjoining pixels along the trajectory of motion. Through this model, a scene from original motion picture without disturbance is transformed into the still image with simulated disturbance. The integration of the light emission from adjoining pixels through the window, also functions as a built-in spatial low pass filter to secure the robust output, considering the MTF of the human eye. Both simulation and actual 42-in-diagonal PDPs showed close results under various conditions, showing that the model is simple, but reasonable. Through the simulation, general properties of the subfield driving scheme for gray scale have been elucidated. For example, a PWM-like coding offers a better performance than an MSB-split coding in many cases. The simulation also exemplifies the motion picture disturbance as a non-linear filter process caused by the dislocation of bit weightings, suggesting that tradeoffs between disturbance and resolution in motion area are mandatory.

This paper describes a classification method for rotated and scaled textured images using invariant parameters based on spectral-moments. Although it is well known that rotation invariants can be derived from moments of grey-level images, the use is limited to binary images because of its computational unstableness. In order to overcome this drawback, we use power spectrum instead of the grey levels to compute moments and adjust the integral region of moment evaluation to the change of scale. Rotation and scale invariants are obtained as the ratios of the different rotation invariants on the basis of a spectral-moment property with respect to scale. The effectiveness of the approach is illustrated through experiments on natural textures from the Brodatz album. In addition, the stability of the invariants with respect to the change of scale is discussed theoretically and confirmed experimentally.

We introduce an image contour clustering method based on a multiscale image representation and its application to image compression. Multiscale gradient planes are obtained from the mean squared sum of 2D wavelet transform of an image. The decay on the multiscale gradient planes across scales depends on the Lipshitz exponent. Since the Lipshitz exponent indicates the spatial differentiability of an image, the multiscale gradient planes represent smoothness or sharpness around edges on image contours. We apply vector quatization to the multiscale gradient planes at contours, and cluster the contours in terms of represntative vectors in VQ. Since the multiscale gradient planes indicate the Lipshitz exponents, the image contours are clustered according to its gradients and Lipshitz exponents. Moreover, we present an image recovery algorithm to the multiscale gradient planes, and we achieve the skech-based image compression by the vector quantization on the multiscale gradient planes.

In this paper, we propose a new approach for describing image patterns. We integrate the concepts of multiscale image analysis, aura matrix (Gibbs random fields and cooccurrences related statistical model of texture analysis) to define image features, and to obtain the features having robustness with illumination variations and shading effects, we analyse images based on the Topographic Structure described by the Surface-Shape Operator, which describe gray-level image patterns in terms of 3D shapes instead of intensity values. Then, we illustrate usefulness of the proposed features with texture classifications. Results show that the proposed features extracted from multiscale images work much better than those from a single scale image, and confirm that the proposed features have robustness with illumination and shading variations. By comparisons with the MRSAR (Multiresolution Simultaneous Autoregressive) features using Mahalanobis distance and Euclidean distance, the proposed multiscale features give better performances for classifying the entire Brodatz textures: 112 categories, 2016 samples having various brightness in each category.

This paper addresses the optimum routing problem of multipoint connection in large-scale networks. A number of algorithms for routing of multipoint connection have been studied so far, most of them, however, assume the availability of complete network information. Herein, we study the problem under the condition that only partial information is available to routing nodes and that routing decision is carried out in a distributed cooperative manner. We consider the network being partitioned into clusters and propose a cluster-based routing approach for multipoint connection. Some basic principles for network clustering are discussed first. Next, the original multipoint routing problem is defined and is divided into two types of subproblems. The global optimum multicast tree then can be obtained asymptotically by solving the subproblems one after another iteratively. We propose an algorithm and evaluate it with computer simulations. By measuring the running time of the algorithm and the optimality of resultant multicast tree, we show analysis on the convergent property with varying network cluster sizes, multicast group sizes and network sizes. The presented approach has two main characteristics, 1) it can yield asymptotical optimum solutions for the routing of multipoint connection, and 2) the routing decisions can be made in the environment where only partial information is available to routing nodes.

Antidiffusion is a process running the diffusion equation reversely in the time domain. Though extremely important for image restoration of the Gaussian blur, it is a horribly ill-posed problem, since minor noise leads to very erroneous results. To solve this ill-posed problem stably, in this paper we first apply a multiscale method to decompose images into various scale components using the Gaussian and Laplacian of Gaussian (LOG) filters. We then show that the restored images can be reconstructed from the components using shrunk Gaussian and LOG filters. Our algorithm has a closed form solution, and is robust to noise because it is performed by the integration computation (convolution), contrasting with the differential computation required by direct discretization of the antidiffusion equation. The antidiffusion algorithm is also computationally efficient since the convolution is row and column separable. Finally, a comparison between the algorithm and the well-known Wiener filter is conducted. Experiments show that our algorithm is really stable and images can be restored satisfactorily.

A Bitplane Tree Weighting (BTW) method with arithmetic coding is proposed for lossless coding of gray scale images, which are represented with multiple bitplanes. A bitplane tree, in the same way as the context tree in the CTW method, is used to derive a weighted coding probability distribution for arithmetic coding with the first order Markov model. It is shown that the proposed method can attain better compression ratio than known schemes with MDL criterion. Furthermore, the BTW method can be extended to a high order Markov model by combining the BTW with the CTW or with prediction. The performance of these modified methods is also evaluated. It is shown that they attain better compression ratio than the original BTW method without increasing memory size and coding time, and they can beat the lossless JPEG coding.

This paper proposes a general expansion architecture for constructing large-scale multicast ATM switches with any type of small multicast switch, called the multicast Universal Multistage Interconnection Network (multicast UniMIN). The proposed architecture consists of a buffered distribution network that can perform cell routing and replication simultaneously, and a column of output switch modules (OSMs). The adoption of channel grouping and virtual first-in-first-out (FIFO) buffers results in high delay/throughput performance, and the distributed lookup table scheme for multicast addressing greatly reduces the size of a single lookup table. Analytical and simulation results show that high delay/throughput performance is obtained for both unicast and multicast traffic, and the proposed architecture yields an even better performance for multicast traffic than for unicast traffic. In addition, the multicast UniMIN switch has such good features as modular expandability, simple hardware, and no internal speed-up operation.

Advanced scientific and engineering problems require massively parallel computing. Critical to the designand ultimately the performanceof such computing systems is the interconnection network binding the computing elements, just as is the cardiovascular network to the human body. This paper develops a new interconnection network, "Tori connected mESHes (TESH)," consisting of k-ary n-cube connection of supernodes that comprise meshes of lower level nodes. Its key features are the following: it is hierarchical, thus allowing exploitation of computation locality as well as easy expansion (up to a million processors), and it appears to be well suited for 3-D VLSI implementation, for it requires far fewer number of vertical wires than almost all known multi-computer networks. Presented in the paper are the architecture of the new network, node addressing and message routing, 3-D VLSI/ULSI considerations, and application of the network to massively parallel computing. Specifically, we discuss the mapping on to the network of stack filtering, a hardware oriented technique for order statistic image filtering.

The pattern spectrum has been proposed to represent morphological size distribution of an image. However, the conventional pattern spectrum cannot extract approximate shape information from image objects spotted by noisy pixels since this is based only on opening. In this paper, a novel definition of the pattern spectrum, morphological multiresolution pattern spectrum (MPS), involving both opening and closing is proposed. MPS is capable of distinguishing details from approximate information of the image.

The authors previously proposed a reconfigurable architecture called the "XL-scheme" in order to cope with processor element (PE) faults as well as link faults. However, they described an algorithm for compensating only for link faults. They determined the potential ability to tolerate faults of the XL-scheme for simultaneous faults of links and PEs, and left a reconstruction algorithm for simultaneous PE and link faults to be studied in the future. This paper briefly explains the XL-scheme and gives a reconstruction algorithm for simultaneous PE and link faults. The algorithm first replaces faulty PEs with healthy ones and then replaces faulty links with healthy ones. We then compute the reliabilities of the mesh-arrays with simultaneous PE and link faults by simulation. We compare the reliability of the XL-scheme with that of the one-and-half track switch model. It is seen that the former is much larger than the latter. Furthermore, we show the result for processing time.

When moving images are displayed on color PDPs, motional artifacts such as disturbances of gray scales and colors are often observed. Reduction of the disturbances is essential in achieving PDPs with acceptable picture quality for TV use. The moving picture quality has been improved by using a modified-binary-coded light-emission-period scheme and a 3dimensional (2D in space and 1D in time) scattering technique. In the 10-sub-field modified-binary-code scheme for 256 gray level expression, sub-field B (of period equivalent to 64) and C (128) of conventional 8-sub-field binary-coded scheme are added and then re-distributed into four sub-fields D (48). The modifiedbinary-coded scheme therefore has the light-emitting-period ratio 1:2:4:8:16:32:48:48:48:48. The maximum period, 128 of the conventional, is reduced to 48. By using the modified-binary-coded scheme, the motional artifacts are reduced significantly, but still perceptible because they appear in forms of continuous lines. In order to make the disturbance less conspicuous, a 3D scattering technique is introduced. The technique has been made possible because of the redundancies of the modified-binary-coded scheme: namely, (1) the position of sub-field-block A (63) can be placed at one of the five positions among four sub-fields D (48), (2) there are various choices when newly assigning one of the four sub-fields D, (3) one can arbitrarily choose whether or not to assign a new sub-field D between the gray levels 48-63, 96-111, 144-160, and 192-207. By randomly selecting one of these emission patterns, the disturbances change their forms from continuous lines to scattered dots. The randomization can be performed at each horizontal line of the display, at each vertical line, at each pixel, of at each TV field. An appreciable improvement of moving picture quality has been realized without influencing the still image.

In this paper we propose two methods, named the time smoothing and the scale smoothing respectively, to reduce the Gibbs overshoot in continuous wavelet transform. In is shown that for a large kind of wavelets the scale smoothing cannot remove the Gibbs overshoot completely as in the case of Fourier analysis, but it is possible to reduce the overshoot for any wavelets by choosing the smoothing window functions properly. The frequency behavior of scale smoothing is similar to that of the time smoothing. According to its frequency behavior we give the empirical conditions for selecting the smoothing window functions. Numerical examples are given for illustrations.

In this paper, in order to achieve the low power consumption of programmable divider in a PLL frequency synthesizer, we propose a new prescaler method for low power consumption. A fixed prescaler is inserted in front of the (N +1/2) programmable divider which is designed based on the new principle. The divider ratio in the loop does not vary at all even if such a prescaler is utilized. Then the permissible delay periods of a programmable divider can be extended to two times as long as the conventional method, and the low power consumption and low cost in a PLL frequency synthesizer have been achieved.

When an image of a 3D object is transmitted or recorded, its range image as well its grey-scale image are required. In this paper, we propose a method of coding for efficient compression of a pair of a pair of range and grey-scale images of 3D objects. We use Lambertian reflection optical model to model the relationship between a 3D object shape and it's brightness. Good illuminant direction estimation leads to good grey-scale image generation and furthermore effects compression results. A method for estimating the illuminant derection and composite albedo from grey-scale image statistics is presented. We propose an approach for estimating the slant angle of illumination based on an optical model from a pair of range and grey-scale images. Estimation result shows that our approach is better. Using the estimated parameters of illuminant direction and composite albedo a synthetic grey-scale image is generated. For comparison, a comparison coding method is used, in which we assume that the range and grey-scale images are compressed separately. We propose an efficient compression coding method for a pair of range and grey-scale images in which we use the correlation between range and grey-scale images, and compress them together. We also evaluate the coding method on a workstation and show numerical results.

The robust statistics has recently been adopted by the computer vision community. Various robust approaches in the computer vision research have been proposed in the last decade for analyzing the image motion from the image sequence. Because of the frequent violation of the Gaussian assumption of the noise and the motion discontinuities due to multiple motions, the motion estimates based on the straightforward approaches such as the least squares estimator and the regularization often produces unsatisfactory result. Robust estimation is a promising approach to deal with these problems because it recovers the intrinsic characteristics of the original data with the reduced sensitivity to the contamination. Several previous works exist and report some isolated results, but there has been no comprehensive analysis. In this paper robust approaches to the optical flow estimation based on the maximum likelihood estimators are proposed. To evaluate the performance of the M-estimators for estimating the optical flow, comparative studies are conducted for every possible combinations of the parameters of three types of M-estimators, two types of residuals, two methods of scale estimate, and two types of starting values. Comparative studies on synthetic data show the superiority of the M-estimator of redescending ψ-function using the starting value of least absolute residuals estimator using Huber scale iteration, in comparison with the other M-estimators and least squares estimator. Experimental results from the real image experiments also confirm that the proposed combinations of the M-estimators handle the contaminated data effectively and produce the better estimates than the least squares estimator or the least absolute residuals estimator.