'Standard deviations suppresses noise' diaporamas de présentation

CS558 Computer Vision

CS558 Computer Vision. Lecture IV : Image Filter and Edge Detection. Slides adapted from S. Lazebnik. Recap of Lecture III. Light and Shade Radiance and irradiance Radiometry of thin lens Bidirectional reflectance distribution function (BRDF) Photometric stereo Color What is color?

933 views • 79 slides

Linear filtering

Linear filtering. Overview: Linear filtering. Linear filters Definition and properties Examples Gaussian smoothing Separability Applications Denoising Non-linear filters: median filter Sharpening Subsampling. Images as functions. Source: S. Seitz. Images as functions.

1.82k views • 69 slides

Lecture 2: Edge detection and resampling

CS6670: Computer Vision. Noah Snavely. Lecture 2: Edge detection and resampling. From Sandlot Science. Administrivia. New room starting Thursday: HLS B11. Administrivia. Assignment 1 (feature detection and matching) will be out Thursday Turning via CMS: https://cms.csuglab.cornell.edu/

841 views • 66 slides

Edge Detection

773 views • 59 slides

Templates and Image Pyramids

09/05/13. Templates and Image Pyramids. Computational Photography Derek Hoiem, University of Illinois. Administrative stuff. Start working on project 1 (due Sept 16) Make sure you can get a project page up Can now complete first part (hybrid images ) Matlab /algebra tutorial

558 views • 45 slides

Linear filtering

545 views • 44 slides

Linear filtering

577 views • 44 slides

Lecture 2: Convolution and edge detection

CS4670: Computer Vision. Noah Snavely. Lecture 2: Convolution and edge detection. From Sandlot Science. Gaussian Kernel. Source: C. Rasmussen. Mean vs. Gaussian filtering. Gaussian filters. = 1 pixel. = 10 pixels. = 30 pixels. = 5 pixels. Gaussian filter.

1.06k views • 29 slides