English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62805/95882 (66%)
Visitors : 3959425      Online Users : 254
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/35083

    Title: Fast bitmap images resizing based on human visual system
    Other Titles: 基於視覺反應之快速影像縮小與放大
    Authors: 黃連進;Hwang, Lain-jinn
    Contributors: 淡江大學資訊工程學系博士班
    趙榮耀;Chao, Louis R.
    Keywords: 人類視覺系統;視覺尖銳區域;影像縮放;多項式片段趨近法;像點複製;隨機像點複製;羅森編碼;Human Visual System;Region Of Sharp Area;Image Resize;Piecewise Polynomial Approximation;Pixel Replication;Random Pixel Replication;Rothstein code
    Date: 2005
    Issue Date: 2010-01-11 05:59:31 (UTC+8)
    Abstract: 人類視覺在影像處理扮演重要關鍵。然而,依據幾何光學,我們發現眼睛並不是一個完美的光學系統,它的清晰區域非常小。所以,設計完美的影像產生系統,如果超出眼睛所能感知的能力,將會造成浪費。

    Human Visual System plays an important factor in image processing.
    However, based on geometric optics, we found the eye is not a
    perfect optical system; its “Region of Sharp Area” is very small.
    Therefore, it would be wasteful to design a system with perfect image render of which the eye could not utilize.

    Based on this result, we introduce three kinds of applications.
    First, we investigated a “Region Of Sharp Area” render, with this scheme,
    we have successfully speeded up the 3D scenes generation. Secondly, we
    proposed a “Multiple Resolution Image Compression” algorithm,
    with this method, we have successfully improved the image compression ratio.
    Thirdly, we develop a fast image resizing scheme that produces
    significantly improved quality over the pixel replication method.
    This algorithm is suitable for real-time image resizing applications
    including: Virtual Reality, Optical Character Recognition, Symbol Recognition, and Car License Plate Recognition. Although this method produced “jaggies” at the edges in the resized image, the execution time is about 22 to 40 times fast than the Windows and the Weiman scheme, respectively. This scheme doesn''t use floating-point operations and buffer area, so, it is suitable for image viewer based on embedded system, such as Portable Digital Assistant.
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Thesis

    Files in This Item:

    File Description SizeFormat
    摘要.pdf371KbAdobe PDF118View/Open
    目次.pdf504KbAdobe PDF96View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback