Conference Paper

Determining Multiscale Image Feature Angles from Complex Wavelet Phases

Department of Engineering, University of Cambridge, Cambridge, England, United Kingdom
DOI: 10.1007/11559573_61 Conference: Proceedings
Source: DBLP


In this paper, we introduce a new multiscale representation for 2-D images named the inter-coefficient product (ICP). The ICP is a decimated pyramid of complex values based on the dual-tree complex wavelet transform (DT-CWT). The complex phases of its coefficients correspond to the angles of dominant directional features in their support regions. As a sparse representation of this information, the ICP is relatively simple to calculate and is a computationally efficient representation for subsequent analysis in computer vision activities or large data set analysis. Examples of ICP decomposition show its ability to provide an intuitive representation of multiscale features (such as edges and ridges). Its potential uses are then discussed

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Available from: Julien Fauqueur, Jul 16, 2014
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    • "A relatively simple and computationally efficient representation of the coefficient phases of the DT-CWT coefficients provided access to the angles of dominant directional features in their support regions. These consist of the so-called Inter Coefficient Products (ICP) (Anderson et al., 2005) which are computed by measuring the relative phase of appropriate neighbor coefficients for the oriented sub-bands considered. These ICP coefficients are then used to construct Texture Orientation Maps (TOM) as illustrated in Fig. 2. "
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    • "Some other applications exploit the local phase information across scales of the complex wavelet such as the description of texture images [8], the detection of blurred images [9] and object recognition [10]. The investigation of local phase in the same orientation and the same scale is based on the dual-tree complex wavelet transform [11] and the complex directional filter bank (CDFB) [12]. Therefore an accurate statistical model of the phase of the complex wavelet coefficients can be beneficial to the developments in the image processing community. "
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    • "In addition, the coefficient phases across scales at an edge are aligned [4], [5]. These intrascale and interscale relationships have been used in some image-processing applications (e.g., in [3]–[7]). All of these point out the significance of the magnitude and phase information of complex coefficients. "
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