Song Jin-ping, Yang Xiao-yi, Hou Yu-hua. The Eno-haar Wavelet Transforms Based on Differential Operators and Its Application[J]. Journal of Electronics & Information Technology, 2004, 26(6): 940-944.
Citation:
Song Jin-ping, Yang Xiao-yi, Hou Yu-hua. The Eno-haar Wavelet Transforms Based on Differential Operators and Its Application[J]. Journal of Electronics & Information Technology, 2004, 26(6): 940-944.
Song Jin-ping, Yang Xiao-yi, Hou Yu-hua. The Eno-haar Wavelet Transforms Based on Differential Operators and Its Application[J]. Journal of Electronics & Information Technology, 2004, 26(6): 940-944.
Citation:
Song Jin-ping, Yang Xiao-yi, Hou Yu-hua. The Eno-haar Wavelet Transforms Based on Differential Operators and Its Application[J]. Journal of Electronics & Information Technology, 2004, 26(6): 940-944.
In this paper, the differential operators are introduced firstly. Then based on the characteristics of Haar wavelet transforms and the differential operators, a transmissibility algorithm is proposed and applied to the singularity measuring of 2D signal. Secondly, a new algorithm called the Eno-haar (Essentially non-oscillatory-haar) wavelet transforms algorithm based on the differential operators is presented. And it is proved by experiments that this algorithm is effective and feasible to image compression.
Hao-Min Zhou.Wavelet transforms and PDE techniques in image compression [D].University of California,2000.[2]Donobo D.De-noising by soft thresholding [J].IEEE Trans.on Info.Theory,1995,41(3):612-627.[3]Ingrid Daubechies.Ten Lectures on Wavelets [M].Philadelphia,Pennsylvania,SIAM,1992,Chap.1～Chap.5.[4]章毓晋.图象分割[M].北京:科学出版社,2001,第二章.[5]Kirsch R.Computer determination of the constituent structure of biological images [J].Computer Biomedical Research.1971,4(3):315-328
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