NDLI: Factoring two-dimensional two-channel non-separable stripe filter banks into lifting steps

Content Provider	IET Digital Library
Author	Liu, Bin Liu, Weijie
Abstract	Since the division with remainder cannot be implemented in multivariable polynomials, the two-dimensional non-separable wavelet transform cannot be lifted by using a similar way as that of univariate wavelet transforms. To solve this problem, a general lifting factoring method of two-dimensional two-channel non-separable stripe filter banks is presented. The constructing form of the polyphase matrices of the stripe filter banks is deduced and the general factoring of the polyphase matrices is given. Compared with the separable lifting wavelet transform, the proposed lifting factoring method can extract better texture information. The lifting form is more succinct than that of the tensor product lifting wavelet transform. The computation amount of the proposed factoring method for image decomposition is a quarter of the two-dimensional two-channel non-separable stripe filter bank and the original two-dimensional two-channel non-separable wavelet system is quickened. Moreover, the proposed lifting factorising method is faster than the traditional two-dimensional two-channel non-separable wavelet transform based on the Fourier transformation framework in which the size of each filter is greater than N + 1 . The proposed lifting factorising method has better sparsity than that of the original wavelet transform and the famous two-dimensional two-channel biorthogonal symmetric non-separable wavelet transform.
Starting Page	1185
Ending Page	1194
Page Count	10
ISSN	17519659
Volume Number	12
e-ISSN	17519667
Issue Number	Issue 7, Jul (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/12/7
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2017.0935
Journal	IET Image Processing
Publisher Date	2018-02-22
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Algebra Channel Bank Filter Computer Vision And Image Processing Technique Feature Extraction Filtering Method in Signal Processing Fourier Transformation Framework Fourier Transforms General Lifting Factoring Method Image Decomposition Image Filtering Image Recognition Image Texture Integral Transforms Matrix Algebra Multivariable Polynomials Polyphase Matrix Tensor Product Lifting Wavelet Transform Texture Information Extraction Two-dimensional Nonseparable Wavelet Transform Two-dimensional Two-channel Biorthogonal Symmetric Nonseparable Wavelet Transform Two-dimensional Two-channel Nonseparable Stripe Filter Bank Factoring Two-dimensional Two-channel Nonseparable Wavelet System Univariate Wavelet Transforms
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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