Multi-level Fractal Decomposition Based Feature Extraction Using Two Dimensional Discrete Wavelet Transforms
نویسندگان
چکیده
In this paper, the multifractal scheme provides a richer framework to extract the fractal components using 2D discrete wavelet transform than that of the conventional methods. In general, most of the signals and images are complex objects and possess a high degree of redundant information. The statistical properties of signals and natural images reveal that natural images can be viewed through different segments, which are most probably fractal components in nature. Such Fractal Components are very informative about the geometry of the images from which they were extracted. Those Components are usually equal to edges present in the Image. The discrete wavelet transform analysis is used for extracting the most revealing parts of the images using such as Haar and Daubechies wavelets. The key advantage of Discrete Wavelet transform over Fourier transforms is temporal resolution characteristic. The Wavelet transform 850 Amitabh Wahi and S. Sundaramurthy captures both location and frequency information. The statistical properties of the extracted fractal components can be used for signal analysis, image reconstruction and object recognition in the multi environment digital images.
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تاریخ انتشار 2014