基于微分算子的Eno-haar小波變換及其應(yīng)用
The Eno-haar Wavelet Transforms Based on Differential Operators and Its Application
-
摘要: 該文首先引入微分算子并結(jié)合Haar小波的特點，提出了一種遺傳性算法，用于2D信號奇異性檢測。其次，將該算法與Eno-haar(Essentially non-oscillatory-haar)小波相結(jié)合，得到了一種基于微分算子的Eno-haar小波變換算法，并通過仿真實驗說明了其在圖像壓縮中的可行性和有效性。
-
關(guān)鍵詞:
- Eno-haar小波變換;微分算子;信號奇異性檢測;圖像壓縮
Abstract: 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]章毓晉.圖象分割[M].北京:科學(xué)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 -
計量
- 文章訪問數(shù): 2332
- HTML全文瀏覽量: 109
- PDF下載量: 723
- 被引次數(shù): 0
下載:
