The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Voi. XXXVII. Part B7. Beijing 2008
1266
5. CONCLUSION
The study of the weighting image fusion based on wavelet
transformation, on the basis of studying the general weighing
methods, proposes a new thought: different fusion rules will be
used in low frequency image and high frequency image. The
simple weighted average in low frequency uses; as for high
frequency, according to the image statistical property, a fusion
method, based on the biggest criterion of partial region standard
deviation, is designed to carry on the processing . The
experimental result has indicated the validity and the usability
of this method.
The study of image fusion by combining the wavelet
transformation with the feature of human vision system, on the
basis of analysis the characteristic of vision contrast gradient,
creates a kind of measure substitution block variance of
measuring the image block uniformity. Then on this basis, a
new fusion rule is proposed. It can be seen, from the fusion
image and the quantification appraisal result, that a satisfactory
fusion effect will be achieved by using the auto-adapted
threshold value to carry on the dynamic fusion.
REFERENCES
[1] ZHAO Zong-gui. An introduction to data fusion method,
first press. 28th institute of electricity ministry, 1998
[2] JIA Yong-hong , Li de-ren , SUN Jia-bing. Multi
dimensional remote sensing imagery data fusion. Remote
sensing technology and application2000,15 (l):41-44
[3] LIU Xiao-long. Study on multi-resource remote sensing
imagery information maintaining fusion technology. Journal of
image and graphics,2001, 6 (7):636-641
[4] LI Jun, LIN Zong-jian. Remote sensing imagery data fusion
method based on the characteristic. Journal of image and
graphics, 1997, 2 (2): 103-107
[5] David A Y. Image Merging and Data Fusion by Means of
the Discrete Two-Dimensional Wavelet Transform.
J.OptSoc. Am. A, 1995,12(9): 1834-1841
[6] CUI Yan-mei, N1 Guo-qiang . AHONG Yan-li et al.
Analysis and evaluation on the imagery fusion effect using
statistical characteristic. Transactions of Beijing Institute of
technology,2000, 20 (1): 102-106
[7] Nunez J,Otazu X,Fors 0,Prades A,Pala V,Arbiol R. Multi
resolution- based image fusion with additive wavelet
transformation. IEEE Transactions on Geosciences and Remote
Sensing, 1999, 37(3): 1204-1211
[8] Mallat S G. A theory for multi-resolution signal
transformation: the wavelet representation. IEEE Transactions
on Pattern Analysis and Machine Intelligence,1989,1 1 (7) :674-
693
[9] Nikhil R. Pal,Sankar K. Pal. A review of image
segmentation techniques[J] Pattern Recognition, 1993, 26(9):
1277-1294
[10] HUANG Ji-wu , Y Q Shi, DAI Xian-hua. Decollate
coding algorithm based on characteristic of vision system.
Journal of image and graphics, 1999.4(51: 400-404
[11] LIU Chun-heng, ZHOU Dong-hua. An adaptive threshold
selection method during failure surveying. Journal of Shanghai
maritime university,2001,.22(3) :46-50
