In image processing, a Gabor filter, named after Dennis Gabor, is a linear filter used for texture analysis, which essentially means that it analyzes whether there is any specific frequency content in the image in specific directions in a localized region around the point or region of analysis. Frequency and orientation representations of Gabor filters are claimed by many contemporary vision scientists to be similar to those of the human visual system. They have been found to be particularly appropriate for texture representation and discrimination. In the spatial domain, a 2-D Gabor filter is a Gaussian kernel function modulated by a sinusoidal plane wave (see Gabor transform). Some authors claim that simple cells in the visual cortex of mammalian brains can be modeled by Gabor functions. Thus, image analysis with Gabor filters is thought by some to be similar to perception in the human visual system. (Wikipedia).
Introduction to Frequency Selective Filtering
http://AllSignalProcessing.com for free e-book on frequency relationships and more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. Separation of signals based on frequency content using lowpass, highpass, bandpass, etc filters. Filter g
From playlist Introduction to Filter Design
From playlist filter (less comfortable)
Karlheinz Gröchenig: Gabor Analysis and its Mysteries (Lecture 1)
The lecture was held within the framework of the Hausdorff Trimester Program Mathematics of Signal Processing. In Gabor analysis one studies the construction and properties of series expansions of functions with respect to a set of time-frequency shifts (phase space shifts) of a single fu
From playlist HIM Lectures: Trimester Program "Mathematics of Signal Processing"
reaLD 3D glasses filter with a linear polarising filter
This is for a post on my blog: http://blog.stevemould.com
From playlist Everything in chronological order
Karlheinz Gröchenig: Gabor Analysis and its Mysteries (Lecture 4)
The lecture was held within the framework of the Hausdorff Trimester Program Mathematics of Signal Processing. In Gabor analysis one studies the construction and properties of series expansions of functions with respect to a set of time-frequency shifts (phase space shifts) of a single f
From playlist HIM Lectures: Trimester Program "Mathematics of Signal Processing"
Romanos Malikiosis: Full spark Gabor frames in finite dimensions
Romanos Malikiosis: Full spark Gabor frames in finite dimensions Abstract: The lecture was held within the framework of the Hausdorff Trimester Program Mathematics of Signal Processing. Gabor frame is the set of all time-frequency translates of a complex function and is a fundamental too
From playlist HIM Lectures: Trimester Program "Mathematics of Signal Processing"
Why Use Kalman Filters? | Understanding Kalman Filters, Part 1
Download our Kalman Filter Virtual Lab to practice linear and extended Kalman filter design of a pendulum system with interactive exercises and animations in MATLAB and Simulink: https://bit.ly/3g5AwyS Discover common uses of Kalman filters by walking through some examples. A Kalman filte
From playlist Understanding Kalman Filters
Nicki Holighaus: Time-frequency frames and applications to audio analysis - Part 1
Find this video and other talks given by worldwide mathematicians on CIRM's Audiovisual Mathematics Library: http://library.cirm-math.fr. And discover all its functionalities: - Chapter markers and keywords to watch the parts of your choice in the video - Videos enriched with abstracts, b
From playlist Analysis and its Applications
Jean-Claude Risset: Sound, music and wavelets in Marseille: A reminder of early sonic [...]
Find this video and other talks given by worldwide mathematicians on CIRM's Audiovisual Mathematics Library: http://library.cirm-math.fr. And discover all its functionalities: - Chapter markers and keywords to watch the parts of your choice in the video - Videos enriched with abstracts, b
From playlist 30 years of wavelets
A PRG for Gaussian Polynomial Threshold Functions - Daniel Kane
Daniel Kane Harvard University March 15, 2011 We define a polynomial threshold function to be a function of the form f(x) = sgn(p(x)) for p a polynomial. We discuss some recent techniques for dealing with polynomial threshold functions, particular when evaluated on random Gaussians. We sho
From playlist Mathematics
Karlheinz Gröchenig: Gabor Analysis and its Mysteries (Lecture 2)
Due to technical problems the blackboard is not visible. The lecture was held within the framework of the Hausdorff Trimester Program Mathematics of Signal Processing. In Gabor analysis one studies the construction and properties of series expansions of functions with respect to a set of
From playlist HIM Lectures: Trimester Program "Mathematics of Signal Processing"
Thomas Serre: "Deep Learning in the Visual Cortex, Pt. 2"
Graduate Summer School 2012: Deep Learning, Feature Learning "Deep Learning in the Visual Cortex, Pt. 2" Thomas Serre, Brown University Institute for Pure and Applied Mathematics, UCLA July 25, 2012 For more information: https://www.ipam.ucla.edu/programs/summer-schools/graduate-summer-
From playlist GSS2012: Deep Learning, Feature Learning
Bruno Olshausen: "From Natural Scene Statistics to Models of Neural Coding & Representation, Pt. 2"
Graduate Summer School 2012: Deep Learning, Feature Learning "From Natural Scene Statistics to Models of Neural Coding & Representation, Pt. 2" Bruno Olshausen, UC Berkeley Institute for Pure and Applied Mathematics, UCLA July 25, 2012 For more information: https://www.ipam.ucla.edu/pro
From playlist GSS2012: Deep Learning, Feature Learning
Bruno Olshausen: "From Natural Scene Statistics to Models of Neural Coding & Representation, Pt. 1"
Graduate Summer School 2012: Deep Learning, Feature Learning "From Natural Scene Statistics to Models of Neural Coding & Representation, Pt. 1" Bruno Olshausen, UC Berkeley Institute for Pure and Applied Mathematics, UCLA July 24, 2012 For more information: https://www.ipam.ucla.edu/pro
From playlist GSS2012: Deep Learning, Feature Learning
Martin Vetterli: Wavelets and signal processing: a match made in heaven
Find this video and other talks given by worldwide mathematicians on CIRM's Audiovisual Mathematics Library: http://library.cirm-math.fr. And discover all its functionalities: - Chapter markers and keywords to watch the parts of your choice in the video - Videos enriched with abstracts, b
From playlist 30 years of wavelets
Stéphane Mallat: "Scattering Invariant Deep Networks for Classification, Pt. 1"
Graduate Summer School 2012: Deep Learning, Feature Learning "Scattering Invariant Deep Networks for Classification, Pt. 1" Stéphane Mallat, École Polytechnique Institute for Pure and Applied Mathematics, UCLA July 18, 2012 For more information: https://www.ipam.ucla.edu/programs/summer
From playlist GSS2012: Deep Learning, Feature Learning
Karlheinz Gröchenig: Gabor Analysis and its Mysteries (Lecture 3)
Due to technical problems the blackboard is not visible. The lecture was held within the framework of the Hausdorff Trimester Program Mathematics of Signal Processing. In Gabor analysis one studies the construction and properties of series expansions of functions with respect to a set of
From playlist HIM Lectures: Trimester Program "Mathematics of Signal Processing"
Stéphane Mallat: "Scattering Invariant Deep Networks for Classification, Pt. 2"
Graduate Summer School 2012: Deep Learning, Feature Learning "Scattering Invariant Deep Networks for Classification, Pt. 2" Stéphane Mallat, École Polytechnique Institute for Pure and Applied Mathematics, UCLA July 18, 2012 For more information: https://www.ipam.ucla.edu/programs/summer
From playlist GSS2012: Deep Learning, Feature Learning