Quaternion wavelet phase based stereo matching for uncalibrated images

Zhou, Jun; Xu, Yi; Yang, Xiaokang

doi:10.1016/j.patrec.2007.03.009

Cited by 40 publications

(20 citation statements)

References 22 publications

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“…We define the phase based edge indicator function by: where α ∈ [0, 1] is a hyperparameter and F A ∈ [0, 1] is the feature asymmetry measure, defined by (6). Thus the values of g are close to one in smooth regions and close to zero near boundaries.…”

Section: Level Set Methods and Front Propagationmentioning

confidence: 99%

“…This uses local phase information derived from the monogenic signal, which is a multidimensional extension of the analytic signal [2], [3], [4]. Phase information has been used in numerous applications in the literature, such as image registration [5], stereo matching [6], filtering [7], enhancement [8], corner and edges detection [9], [10] and segmentation [11], [12], [13], [14]. Phase-based processing has attracted a lot of attention in image analysis, but probably not still enough in ultrasound image segmentation, see [1].…”

Section: Introductionmentioning

confidence: 99%

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Phase-Based Level Set Segmentation of Ultrasound Images

Belaid

Boukerroui

Maingourd

et al. 2011

IEEE Trans. Inform. Technol. Biomed.

134

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Abstract-Ultrasound images segmentation is a difficult problem due to speckle noise, low contrast and local changes of intensity. Intensity based methods do not perform particularly well on ultrasound images. However, it has been previously shown that these images respond well to local phase-based methods which are theoretically intensity-invariant. Here, we use level set propagation to capture the left ventricle boundaries. This uses a new speed term based on local phase and local orientation derived from the monogenic signal, which makes the algorithm robust to attenuation artefact. Furthermore, we use Cauchy kernels, instead of the commonly used log-Gabor, as pair of quadrature filters for the feature extraction. Preliminary results show that the proposed method can robustly handle noise, and captures well the low contrast boundaries.

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Section: Level Set Methods and Front Propagationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Phase-Based Level Set Segmentation of Ultrasound Images

Belaid

Boukerroui

Maingourd

et al. 2011

IEEE Trans. Inform. Technol. Biomed.

134

View full text Add to dashboard Cite

show abstract

“…They also demonstrated a number of properties of these extended wavelets using the classical Fourier transform (FT). In [6], using the (two-sided) QFT Traversoni proposed a discrete quaternion wavelet transform which was applied by Bayro-Corrochano [12] and Zhou et al [13]. Recently, in [18,19], we introduced an extension of the WT to Clifford algebra by means of the kernel of the Clifford Fourier transform [8].…”

Section: Introductionmentioning

confidence: 99%

Two-dimensional quaternion wavelet transform

Bahri

Ashino

Vaillancourt

2011

Applied Mathematics and Computation

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“…By using hypercomplex arithmetic, known algorithms can be improved or extended to 4 dimensions so as to find new applications (Alexiadis & Sergiadis, 2009;Chan et al, 2008;Denis et al, 2007;Ell & Sangwine, 2007;Karney, 2007;Marion et al, 2010;Parfieniuk & Petrovsky, 2010a;Seberry et al, 2008;Took & Mandic, 2010;Tsui et al, 2008;Zhou et al, 2007). Current research is mainly focused on theoretical development of quaternion-based algorithms, but one can expect that, in the course of time, engineers and scientists will implement them in hardware, and thus will need building blocks, design insights, methodologies, and tools.…”

Section: Introductionmentioning

confidence: 99%