EE 445S Real-Time Digital Signal Processing Lab Fall 2011 Lab #3.1 Digital Filters Debarati Kundu (With the help of Mr. Eric Wilbur, TI)
Path Differentials for MC Rendering Frank Suykens Department of Computer Science K.U.Leuven, Belgium Dagstuhl 2001: Stochastic methods in Rendering.
A Signal-Processing Framework for Inverse Rendering Ravi Ramamoorthi Pat Hanrahan Stanford University.
Computer Vision Group Edge Detection Giacomo Boracchi 5/12/2007 [email protected].
Learning and Fourier Analysis Grigory Yaroslavtsev CIS 625: Computational Learning Theory.
HMC St Andrews 5 th October 2011 The 21st Century Learning Initiative .
Graphics&Design Correction and Adjustment - Creative: colour & tone, dust & marks, sharp Tech: Gamma, Histograms, & Convolution.
Week 14. Review 1.Signals and systems 2.State machines 3.Linear systems 4.Hybrid systems 5.LTI systems & frequency response 6.Convolution 7.Fourier Transforms.
Recap from Monday Spectra and Color Light capture in cameras and humans.
Frequency Response After this lesson, you will be able to: 1.Know how complex exponentials are eigenfunctions of LSI. And show how this property leads.
Linear filters and edges. Linear Filters General process: Form new image whose pixels are a weighted sum of original pixel values, using the same set.
EARTHQUAKES (2): WAVEFORM MODELING, MOMENT TENSORS, & SOURCE PARAMETERS Kikuchi and Kanamori, 1991.