基于微分算子的Eno-haar小波变换及其应用
The Eno-haar Wavelet Transforms Based on Differential Operators and Its Application
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摘要: 该文首先引入微分算子并结合Haar小波的特点，提出了一种遗传性算法，用于2D信号奇异性检测。其次，将该算法与Eno-haar(Essentially non-oscillatory-haar)小波相结合，得到了一种基于微分算子的Eno-haar小波变换算法，并通过仿真实验说明了其在图像压缩中的可行性和有效性。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.
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