Wavelet-based diffusion approaches for signal denoising
Signal Processing
A framework for automatic time-domain characteristic parameters extraction of human pulse signals
EURASIP Journal on Advances in Signal Processing
Higher-order properties of analytic wavelets
IEEE Transactions on Signal Processing
The monogenic wavelet transform
IEEE Transactions on Signal Processing
A shearlet approach to edge analysis and detection
IEEE Transactions on Image Processing
On the analytic wavelet transform
IEEE Transactions on Information Theory
Curvature product corner detection in direct curvature scale space
International Journal of Computational Vision and Robotics
Two-dimensional multi-pixel anisotropic Gaussian filter for edge-line segment (ELS) detection
Image and Vision Computing
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Complex-valued wavelets are normally used to measure instantaneous frequencies, while real wavelets are normally used to detect singularities. We prove that the wavelet modulus maxima with a complex-valued wavelet can detect and characterize singularities. This is an extension of the previous wavelet work of Mallat and Hwang on modulus maxima using a real wavelet. With this extension, we can simultaneously detect instantaneous frequencies and singularities from the wavelet modulus maxima of a complex-valued wavelet. Some results of singularity detection with the modulus maxima from a real wavelet and an analytic complex-valued wavelet are compared. We also demonstrate that singularity detection methods can be employed to detect the corners of a planar object.