Impact Assessment Of Mother Wavelet And Number Of Wavelet Decomposition To Estimate Of Change Map By Wavelet Algorithm

Document Type : علمی - پژوهشی

Authors

1 M.Sc of Remote Sensing and GIS, Tarbiat Modares University, Tehran

2 Associate Prof. of GIS Engineering, K.N. Toosi University of Technology

3 Prof. of Electrical & Computer Engineering Faculty, Tarbiat Modares University

Abstract

Change detection methods are powerful tools to present the changes on the Earth’ surface. The multi-scale approaches which proceed the observations at coarser and finer scales, can be applied to maximize the accuracy of the change maps. The multi-scale approach, based on discrete wavelet, has been applied in this research. In addition to the spectral information, the contextual or local information- available in the image are set in the processing. The wavelet technique is exploited in many processing fields of images. The ability of the wavelet technique has been applied for the change-detection, based on the satellite images in this study. The necessary parameters for the wavelet modification are the quantity decomposition levels and kind of mother wavelet. Thus The effect of the mother wavelet boir3/7 and db4 and the levels of  decomposition s=1 to s=6 on the final change detection map have been assessed . All the results have been stated on the basis of the detection accuracy kappa coefficient and overall accuracy. The results reveal the influences of the mother wavelet and levels of decomposition on the final change detection map. The Change detection map, using t bior3/7mother wavelet, reveals higher overall accuracy and better kappa coefficient in proportion to bd4 mother wavelet. It is 0/7966 and 89/8013 for band 3 of Mother wavelet bior3/7 and 9/8013 & 0/7966 for mother wavelet db4. The next parameter being investigated here is related to the analysis surfaces influence on the precision of the change detection map. It increases to the level 3 of analysis and then decrease down. Eventually, most of the overall precision and kappa coefficient is related to the analysis level 3 of both mother wavelet. A comparison has been also conducted between the wavelet technique and the three methods image differencing , image ratio and supervised classification. The final review reveals the priority of the wavelet technique, as it presents better results.

Keywords

References

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Iranian Journal of Remote Sensing & GIS
Volume 8, Issue 2 - Serial Number 2
November 2016
Pages 17-34

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