• Title/Summary/Keyword: Spatial memory

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Unsupervised Image Classification for Large Remotely-sensed Imagery using Regiongrowing Segmentation

  • Lee, Sang-Hoon
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.188-190
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    • 2006
  • A multistage hierarchical clustering technique, which is an unsupervised technique, was suggested in this paper for classifying large remotely-sensed imagery. The multistage algorithm consists of two stages. The local segmentor of the first stage performs regiongrowing segmentation by employing the hierarchical clustering procedure of CN-chain with the restriction that pixels in a cluster must be spatially contiguous. This stage uses a sliding window strategy with boundary blocking to alleviate a computational problem in computer memory for an enormous data. The global segmentor of the second stage has not spatial constraints for merging to classify the segments resulting from the previous stage. The experimental results show that the new approach proposed in this study efficiently performs the segmentation for the images of very large size and an extensive number of bands

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A Implementation of Simple Convolution Decoder Using a Temporal Neural Networks

  • Chung, Hee-Tae;Kim, Kyung-Hun
    • Journal of information and communication convergence engineering
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    • v.1 no.4
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    • pp.177-182
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    • 2003
  • Conventional multilayer feedforward artificial neural networks are very effective in dealing with spatial problems. To deal with problems with time dependency, some kinds of memory have to be built in the processing algorithm. In this paper we show how the newly proposed Serial Input Neuron (SIN) convolutional decoders can be derived. As an example, we derive the SIN decoder for rate code with constraint length 3. The SIN is tested in Gaussian channel and the results are compared to the results of the optimal Viterbi decoder. A SIN approach to decode convolutional codes is presented. No supervision is required. The decoder lends itself to pleasing implementations in hardware and processing codes with high speed in a time. However, the speed of the current circuits may set limits to the codes used. With increasing speeds of the circuits in the future, the proposed technique may become a tempting choice for decoding convolutional coding with long constraint lengths.

Enhanced Prediction Algorithm for Near-lossless Image Compression with Low Complexity and Low Latency

  • Son, Ji Deok;Song, Byung Cheol
    • IEIE Transactions on Smart Processing and Computing
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    • v.5 no.2
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    • pp.143-151
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    • 2016
  • This paper presents new prediction methods to improve compression performance of the so-called near-lossless RGB-domain image coder, which is designed to effectively decrease the memory bandwidth of a system-on-chip (SoC) for image processing. First, variable block size (VBS)-based intra prediction is employed to eliminate spatial redundancy for the green (G) component of an input image on a pixel-line basis. Second, inter-color prediction (ICP) using spectral correlation is performed to predict the R and B components from the previously reconstructed G-component image. Experimental results show that the proposed algorithm improves coding efficiency by up to 30% compared with an existing algorithm for natural images, and improves coding efficiency with low computational cost by about 50% for computer graphics (CG) images.

A Convolutional Decoder using a Serial Input Neuron

  • Kim, Kyunghun;Lee, Chang-Wook;Jeon, Gi-Joon
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.89.1-89
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    • 2002
  • Conventional multilayer feedforward artificial neural networks are very effective in dealing with spatial problems. To deal with problems with time dependency, some kinds of memory have to be built in the processing algorithm. In this paper we show how the newly proposed Serial Input Neuron (SIN) convolutional decoders can be derived. As an example, we derive the SIN decoder for \ulcornerrate code with constraint length 3. The SIN is tested in Gaussian channel and the results are compared to the results of the optimal Viterbi decoder. A SIN approach to decode convolutional codes is presented. No supervision is required. The decoder lends itself to pleasing implementations in hardware and processing...

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Newton-Krylov Method for Compressible Euler Equations on Unstructured Grids

  • Kim Sungho;Kwon Jang Hyuk
    • 한국전산유체공학회:학술대회논문집
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    • 1998.11a
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    • pp.153-159
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    • 1998
  • The Newton-Krylov method on the unstructured grid flow solver using the cell-centered spatial discretization oi compressible Euler equations is presented. This flow solver uses the reconstructed primitive variables to get the higher order solutions. To get the quadratic convergence of Newton method with this solver, the careful linearization of face flux is performed with the reconstructed flow variables. The GMRES method is used to solve large sparse matrix and to improve the performance ILU preconditioner is adopted and vectorized with level scheduling algorithm. To get the quadratic convergence with the higher order schemes and to reduce the memory storage. the matrix-free implementation and Barth's matrix-vector method are implemented and compared with the traditional matrix-vector method. The convergence and computing times are compared with each other.

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An Adaptive Spatial Depth Filter for 3D Rendering IP

  • Yu, Chang-Hyo;Lee, Sup-Kim
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.3 no.4
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    • pp.175-180
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    • 2003
  • In this paper, we present a new method for early depth test for a 3D rendering engine. We add a filter stage to the rasterizer in the 3D rendering engine, in an attempt to identify and avoid the occluded pixels. This filtering block determines if a pixel is hidden by a certain plane. If a pixel is hidden by the plane, it can be removed. The simulation results show that the filter reduces the number of pixels to the next stage up to 71.7%. As a result, 67% of memory bandwidth is saved with simple extra hardware.

Efficiency Enhancement of CFDS Code (CFDS 코드의 효율성 개선)

  • Kim J. G.;Lee J.;Kim C.;Hong S. K.;Lee K. S.;Ahn C. S.
    • 한국전산유체공학회:학술대회논문집
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    • 2005.04a
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    • pp.123-127
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    • 2005
  • The numerical analyses of the complicated flows are widely attempted in these days. Because of the enormous demanding memory and calculation time, parallel processing is used for these problems. In order to obtain calculation efficiency, it is important to choose proper domain decomposition technique and numerical algorithm. In this research we enhanced the efficiency of the CFDS code developed by ADD, using parallel computation and newly developed numerical algorithms. For the huge amount of data transfer between blocks non-blocking method is used, and newly developed data transfer algorithm is used for non-aligned block interface. Recently developed RoeM scheme is adpoted as a spatial difference method, and AF-ADI and LU-SGS methods are used as a time integration method to enhance the convergence of the code. Analyses of the flows around the ONERA M6 wing and the high angle of attack missile configuration are performed to show the efficiency improvement.

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A Study on the Si-SiO$_2$Interface Traps of the Degraded SONOSFET Nonveolatile Memories with the Charge Pumping Techniques (Charge Pumping 기술을 응용한 열화된 SONOSFET 비휘발성 기억소자의 Si-SiO$_2$ 계면트랩에 관한 연구)

  • 김주열;김선주;이성배;이상배;서광열
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 1994.11a
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    • pp.59-64
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    • 1994
  • The Si-SiO$_2$interface trpas of the degraded short-channel SONOSFET memory devices were investigated using the charge pumping techniques. The degradation of devices with write/erase cycle appeared as the increase of the Si-SiO$_2$interface trap density. In order to determine the capture cross-section of the interface trap. I$\_$CP/-V$\_$GL/ characteristic curves were measured at different temperatures. Also, the spatial distributions of Si-SiO$_2$interface trap were examined by the variable-reverse bias boltage method.

AUTOMATIC TEXTURE EXTRACTION FROM AERIAL PHOTOGRAPHS USING THE ZI-BUFFER

  • Han, Dong-Yeob;Kim, Yong-Il;Yu, Ki-Yun;Lee, Hyo-Seong;Park, Byoung-Uk
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.584-586
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    • 2007
  • 3D virtual modeling such as creation of a cyber city or landscape, or making a 3D GIS requires realistic textures. Automatic texture extraction using close range images is not yet efficient or easy in terms of data acquisition and processing. In this paper, common problems associated with automatic texture extraction from aerial photographs are explored. The ZI-buffer, which has depth and facet ID fields, is proposed to remove hidden pixels. The ZI-buffer algorithm reduces memory burden and identifies visible facets. The correct spatial resolution for facet gridding is tested. Error pixels in the visibility map were removed by filtering.

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Multiview Stereoscopic Display based on Volume Holographic Memory (체적 홀로그래픽 메모리를 이용한 다시점 스테레오스코픽 디스플레이)

  • 이승현;손광철;심원섭;양훈기;김은수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.5A
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    • pp.688-695
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    • 2000
  • We present a multi-view autostereoscopic display system based on volume holographic storage technique. In this proposed system, the interference pattern of spatial multiplexed plane reference and angular multiplexed plane object beams are recorded into a photorefractive crystal, which plays a role of guiding object beams of multi-view images into the desired persfective directions. For reconstruction, object beams containing the desired multi-view image information, which satisfy Bragg matching condition, are illuminated in the time-division multiplexed manner onto the crystal. Then multiple stereoscopic images are Projected to the display plane for autostereoscopic 3D viewing.

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