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iMondrian Sparse Stochastic Processes Ricard Delgado, 2011 This app generates artistic representations of Mondrian processes. These processes are named after Piet Mondrian (1872-1944), a great figure in the neoplasticism style known for his grid-based paintings. |
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Michael Rusterholz, 2012 Filter Creator helps you to better understand the mathematics of discrete and continuous audio filters and is particularly aimed at students of signal processing classes.
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If Java is not already installed on your machine your have to visit the Java website and install Java before to run our Java Applet.
Demonstrations showing some of our recent research results in biomedical image processing.
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SURE-LET Wavelet Denoising (in color or in grayscale) A new approach to color or grayscale image denoising. |
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Variational Levelset Spline New formulation of level-set modeling the implicit as a continuous parametric function expressed on a B-spline basis. |
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Steerable Feature Detection General approach for the design of 2-D feature detectors. |
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Extended Depth of Field using the Wavelet Transform Download a program to perform an extended depth of focus of z-stack images to obtain in focus image. |
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Hex-splines A novel spline family for hexagonal lattices. |
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Fractional Splines Wavelets New wavelet bases with a continuously-varying order parameter and ontinuously-varying order and shift parameters. |
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Shifted Linear Interpolation A new method for improving the quality linear interpolation, without any additional cost. |
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Computerized Tomography Simulates the computerized tomography (Radon transform) and performs the reconstruction (filtered backprojection). |
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Comparison of interpolators Compares the standard interpolation functions with the ones developped by the BIG. |
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Fractional Quincunx Wavelets Shows the quincunx transform using filters of fractional order. |
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Resizing The optimal algorithm to resize images. |
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Spline Warping of our staff Bidirectional landmark warping of our staff. |
Demonstrations illustrating some of the techniques described in the Image Processing course.
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Edge Detection Detects edges in an image. |
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Gradient Compares several gradient algorithms. |
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Basis functions of the FFT, DCT and Haar Wavelet Transform |
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Local Normalization Applies a local normalization to an image based on smooth operators. |
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Morphology Operators Basic operators of morphology in binary and gray level images. |
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Smoothing Techniques Compares several methods to smooth an image. |
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Template Matching> Convoles an image with a 3*3 mask to edge detection or with a template model to identity pattern. |
Demonstrations designed by students working in our group.
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Drop Shape Analysis Aurélien Stalder |
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3D Deconvolution in Optical Microscopy Pierre Besson |
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Denoising of Fractal-like images using Polyharmonic B-splines Alex Prudencio |
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Filtering in Fourier Domain Joy Anushini Ariarajah |
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Edge detection with a sub-pixel precision Nicolas Pavillon |
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Complex Fractional Splines Wavelet Florian Luisier |
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Virtual Microscope Christophe Magnard |
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Diffusion Enhancing Methods Alwyn Fernandes |
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Continuous Wavelet Transform using Splines Raphaël Ertle |
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Watershed by flooding Daniel Stadelmann |
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Non Linear Diffusion Filtering Laurent Vieira De Mello |
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Interpolation on Affine Transformation Raphaël Marthe |