Fusion of 2-D SIMS Images Using the Wavelet Transform

被引:0
|
作者
Thomas C. Stubbings
Stavri G. Nikolov
Herbert Hutter
机构
[1]  Institute for Analytical Chemistry,
[2] Vienna University of Technology,undefined
[3] Getreidemarkt 9/151,undefined
[4] Vienna 1060,undefined
[5] Austria,undefined
[6]  Department of Electrical and Electronic Engineering,undefined
[7] University of Bristol,undefined
[8] Merchant Venturers Building,undefined
[9] Woodland Road,undefined
[10] Bristol BS8 1UB,undefined
[11] UK,undefined
来源
Microchimica Acta | 2000年 / 133卷
关键词
Key words: SIMS; multispectral images; image fusion; wavelets; wavelet transform; wavelet transform fusion.;
D O I
暂无
中图分类号
学科分类号
摘要
 Secondary ion mass spectroscopy (SIMS) is a powerful method for element distribution examination of conducting and semi-conducting surfaces at high spatial resolution and with a high sensitivity. Routine surface analysis produces about 8 to 15 images in a short time, each of which displays the intensity distribution of one mass, thus generating a multispectral SIMS image. Formation of occlusions, segregations, and the overall location of the elements relative to each other, are difficult to recognise when looking at n separate 2-D images.
引用
收藏
页码:273 / 278
页数:5
相关论文
共 50 条
  • [1] Fusion of 2-D SIMS images using the wavelet transform
    Stubbings, TC
    Nikolov, SG
    Hutter, H
    MIKROCHIMICA ACTA, 2000, 133 (1-4) : 273 - 278
  • [2] Separation and reproduction of mixed images using 2-D complex wavelet transform
    Matsuura, Tsutomu
    Faiz, Amirul
    Kiryu, Kouji
    PRECISION INSTRUMENTATION AND MEASUREMENT, 2010, 36 : 466 - +
  • [3] A Detection of Defect in Diamond Images Using 2-D Haar Wavelet Transform
    Markchai, Puttipong
    Kiattisin, Supaporn
    Leelasantitham, Adisorn
    INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS 2010), 2010, : 831 - 834
  • [4] Implementation of 2-D biorthogonal wavelet transform using 2-D APDF
    Fu, Qiming
    Zhou, Xiao
    Wang, Chengyou
    Jiang, Baochen
    International Journal of Signal Processing, Image Processing and Pattern Recognition, 2015, 8 (05) : 55 - 74
  • [5] Noise reduction of subsurface radar images using a 2-D parabolic wavelet transform
    Sato, T
    Fuse, E
    IGARSS '98 - 1998 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, PROCEEDINGS VOLS 1-5: SENSING AND MANAGING THE ENVIRONMENT, 1998, : 1760 - 1762
  • [6] Image compression using the 2-D wavelet transform
    Lewis, A. S.
    Knowles, G.
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 1992, 1 (02) : 244 - 250
  • [7] 2-D wavelet transform using the lambda multiplexing technique
    Zalevsky, Z
    Mendlovic, D
    Garcia, J
    17TH CONGRESS OF THE INTERNATIONAL COMMISSION FOR OPTICS: OPTICS FOR SCIENCE AND NEW TECHNOLOGY, PTS 1 AND 2, 1996, 2778 : 433 - 434
  • [8] 2-D Object Recognition Approach using Wavelet Transform
    Kumar, Kamelsh
    Shaikh, Riaz Ahmed
    Arain, Rafaqat Hussain
    Shah, Safdar Ali
    Shaikh, Hidayatullah
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2018, 9 (03) : 231 - 235
  • [9] Fusion of 2-D images using their multiscale edges
    Nikolov, SG
    Bull, DR
    Canagarajah, CN
    Halliwell, M
    Wells, PNT
    15TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 3, PROCEEDINGS: IMAGE, SPEECH AND SIGNAL PROCESSING, 2000, : 41 - 44
  • [10] Fusion of PET and CT images using wavelet transform
    Shalchian, Bahareh
    Rajabi, Hossein
    Soltanian-zadeh, Hamid
    HELLENIC JOURNAL OF NUCLEAR MEDICINE, 2009, 12 (03): : 238 - 243