Feature detection from local energy
Pattern Recognition Letters
Texture features based on Gabor phase
Signal Processing
Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Online Palmprint Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition with local steerable phase feature
Pattern Recognition Letters
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
The Shiftable Complex Directional Pyramid—Part I: Theoretical Aspects
IEEE Transactions on Signal Processing - Part I
Texture image retrieval using new rotated complex wavelet filters
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance
IEEE Transactions on Image Processing
The contourlet transform: an efficient directional multiresolution image representation
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Image Modeling Using Interscale Phase Properties of Complex Wavelet Coefficients
IEEE Transactions on Image Processing
Image Denoising Using Derotated Complex Wavelet Coefficients
IEEE Transactions on Image Processing
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The relative phase is an efficient approach to exploit the phase information of complex wavelet coefficients. However, the relative phase original generated from the pyramidal dual tree directional filter bank (PDTDFB) has three defaults. Firstly, its texture retrieval performance does not simultaneously improve in general as the scale increases. Secondly, it is not accurate enough when the directional subbands are not uniformly downsampled along row and column. Thirdly, its 2^n number of directions are not optimal. In this paper, we propose a new multiscale and multidirection transform for relative phase, named as dual tree shearlets. The transform is based on the discrete shearlet transform, but a dual tree Laplacian pyramid is adopted to create a real-imaginary pair structure for deriving phase information under multiscale framework. The dual tree shearlets have the properties of uniform downsampled subbands; higher directional sensitivity and the 2-D Hilbert transform relationship between two channels like the dual tree complex wavelet transform (DTCWT). The numerical experiments presented in this paper demonstrate that the relative phase of our proposed method outperforms that of the PDTDFB in texture retrieval application both in terms of performance and computational efficiency. The results show that relative phase of the dual tree shearlets amends the above mentioned defaults.