Characterization of Signals from Multiscale Edges

By Stéphane Mallat, S. Zhong. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011

3,384 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/f42d06ff2160dae7412c299619c04f63395b784b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

In Media Technology

Citations in the corpus

Denoising of Dynamic Contrast-Enhanced MR Images Using Dynamic Nonlocal Means (2010, methodology): “The method uses the Mallat and Zhong [ 31 ] wavelets family and is based on the evaluation of scale products which are defined”
Noise Reduction for Magnetic Resonance Images via Adaptive Multiscale Products Thresholding (2003, methodology): “Both of Xu's and Sadler's works are implemented with a dyadic wavelet constructed by Mallat and Zhong [4].”
The lifting scheme: a construction of second generation wavelets (1998, background): “Wavelet probing thus provides an alternative for the zero crossing representation introduced by Mallat and Zhong 82, 83].”
Multiresolution Models for Object Detection (2010, background): “Examples include multiscale edge models [8] and object representations based on multiscale wavelets [9, 10].”
Approaches for automated detection and classification of masses in mammograms (2006, neutral): “Dyadic wavelet [30–32,35–37] 1.”
The redundant discrete wavelet transform and additive noise (2005, background): “As a result, the size of each subband in an RDWT is the exactly the same as that of the input signal, facilitating a number of applications such as feature detection [ 4 , 5], signal denoising [19, 20], motion estimation [6n8], and watermarking [21].”
Detection of PD utilizing digital signal processing methods. Part 3: Open-loop noise reduction (2001, methodology): “Algorithms for selecting the threshold levels include fixed threshold, minimax criteria, Stein’s unbiased risk estimate, or a combination thereof [ 23 ].”
Multiscale image segmentation using wavelet-domain hidden Markov models (2001, background): “Persistence and Clustering: Large/small values of wavelet coe cients tend to propagate across scale in the wavelet quad-tree [26,27].”
Wavelet based real-time smoke detection in video (2005, background): “Edges produce local extrema in wavelet subimages [4], [5].”
Digital Video Quality: Vision Models and Metrics (2005, background): “where is the associated 2-D scaling function (Mallat and Zhong, 1992).”
A Generic and Robust System for Automated Patient-Specific Classification of ECG Signals (2009, methodology): “The fast TI-DWT algorithm, whose computational complexity is O(N logN), can be implemented using a recursive filter tree architecture [27].”
A Mathematical Theory of Deep Convolutional Neural Networks for Feature Extraction (2015, methodology): “Speciﬁcally, with the relation of | f ∗ ψ λ | to the Canny edge detector [46] as described in [31], in as an image at scale j specifying the locations of edges of the image f that are oriented in direction k .”