Multiresolution Analysis for Image by Generalized 2-D Wavelets
Date Issued
2008
Date
2008
Author(s)
Zhang, Yu-Si
Abstract
The most important feature of the wavelet transform is that we can use few waveletoefficients to approximate a signal. Because of this property, JPEG 2000 adopted theavelet transform as a portion of its algorithm.owever, the fundamental theory of this feature was derived from one-dimensionalignals. For two-dimensional signals, we can use “separable wavelet transform” to extendne-dimensional wavelet transform into two-dimensional wavelet transform. Althoughhis method was used widely, it ignored the geometric properties of thewo-dimensional signal such as edges.ince two-dimensional signals have more features, many researchers started toropose a new transform such that the new transform not only has all features of theavelet transform but also exploit the properties of the two-dimensional signals. Furthermore,he performance is better than that of the separable wavelet transform.his thesis focuses on the ideas, advantages, and disadvantages of these newransforms. After discussing these methods, we propose our method to improve the performance.
Subjects
multiresolution analysis
wavelet transform
bandelet transform
curvelet transform
contourlet transform
Type
thesis
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