The Trilateral Filter for High Contrast Images and Meshes

Slides:

Advertisements

Similar presentations

CSCE 643 Computer Vision: Template Matching, Image Pyramids and Denoising Jinxiang Chai.

Advertisements

Image Processing Lecture 4

Accelerating Spatially Varying Gaussian Filters Jongmin Baek and David E. Jacobs Stanford University.

Edges and Scale Today’s reading Cipolla & Gee on edge detection (available online)Cipolla & Gee on edge detection Szeliski – From Sandlot ScienceSandlot.

1 Image Filtering Readings: Ch 5: 5.4, 5.5, 5.6,5.7.3, 5.8 (This lecture does not follow the book.) Images by Pawan SinhaPawan Sinha formal terminology.

1 Image filtering Images by Pawan SinhaPawan Sinha.

CS CS 175 – Week 4 Triangle Mesh Smoothing Discrete Differential Geometry.

Gradient Domain High Dynamic Range Compression

Course 3: Computational Photography Ramesh Raskar Mitsubishi Electric Research Labs Jack Tumblin Northwestern University Course WebPage :

ECE 472/572 - Digital Image Processing Lecture 4 - Image Enhancement - Spatial Filter 09/06/11.

CSCE 441: Computer Graphics Image Filtering Jinxiang Chai.

Tone mapping with slides by Fredo Durand, and Alexei Efros Digital Image Synthesis Yung-Yu Chuang 11/08/2005.

A Gentle Introduction to Bilateral Filtering and its Applications 08/10: Applications: Advanced uses of Bilateral Filters Jack Tumblin – EECS, Northwestern.

G52IIP, School of Computer Science, University of Nottingham What we will learn … Topics relate to the use of computer to Acquire/generate Process/manipulate/store.

Gwangju Institute of Science and Technology Intelligent Design and Graphics Laboratory Feature-Aware Filtering for Point-Set Surface Denoising Min Ki Park*Seung.

Manuel Mesters - Subdivision Surfaces computer graphics & visualization Seminar Computer Graphics Geometric representation and processing: Subdivision.

Surface Reconstruction Using RBF Reporter : Lincong Fang

COLLEGE OF ENGINEERING UNIVERSITY OF PORTO COMPUTER GRAPHICS AND INTERFACES / GRAPHICS SYSTEMS JGB / AAS 1 Shading (Shading) & Smooth Shading Graphics.

Perception Motivated Hybrid Approach to Tone Mapping Martin Čadík Czech Technical University in Prague, Czech Republic.

A Case Study using the Hugh Morton Photograph Collection A Photographic Journey brought to you by the Digital Production Center.

. Wild Dreams for Cameras Jack Tumblin Northwestern University From May 24 Panel Discussion on cameras.

Digital Image Processing

03/05/03© 2003 University of Wisconsin Last Time Tone Reproduction If you don’t use perceptual info, some people call it contrast reduction.

Digital Image Processing CSC331 Image Enhancement 1.

Computer Vision – Enhancement(Part III) Hanyang University Jong-Il Park.

Image Enhancement [DVT final project]

G52IIP, School of Computer Science, University of Nottingham 1 G52IIP Summary Topic 1 Overview of the course Related topics Image processing Computer.

A Gentle Introduction to Bilateral Filtering and its Applications Sylvain Paris – MIT CSAIL Pierre Kornprobst – INRIA Odyssée Jack Tumblin – Northwestern.

Wiener Subdivision Presented by Koray KAVUKCUOGLU Geometric Modeling Spring 2004.

G52IIP, School of Computer Science, University of Nottingham 1 G52IIP 2011 Summary Topic 1 Overview of the course Related topics Image processing Computer.

Geometric Modeling using Polygonal Meshes Lecture 3: Discrete Differential Geometry and its Application to Mesh Processing Office: South B-C Global.

A Gentle Introduction to Bilateral Filtering and its Applications 07/10: Novel Variants of the Bilateral Filter Jack Tumblin – EECS, Northwestern University.

Surround-Adaptive Local Contrast Enhancement for Preserved Detail Perception in HDR Images Geun-Young Lee 1, Sung-Hak Lee 1, Hyuk-Ju Kwon 1, Tae-Wuk Bae.

Bilateral Mesh Denoising Shachar Fleishman Iddo Drori Daniel Cohen-Or Tel Aviv University.

1 Introduction to Computer Graphics with WebGL Ed Angel Professor Emeritus of Computer Science Founding Director, Arts, Research, Technology and Science.

1 Introduction to Computer Graphics with WebGL Ed Angel Professor Emeritus of Computer Science Founding Director, Arts, Research, Technology and Science.

CSE 6367 Computer Vision Image Operations and Filtering “You cannot teach a man anything, you can only help him find it within himself.” ― Galileo GalileiGalileo.

Digital Image Processing CSC331 Image Enhancement 1.

A Gentle Introduction to Bilateral Filtering and its Applications 10/10: Conclusions Jack Tumblin – EECS, Northwestern University.

Image enhancement Last update Heejune Ahn, SeoulTech.

Tone mapping Digital Visual Effects, Spring 2007 Yung-Yu Chuang 2007/3/13 with slides by Fredo Durand, and Alexei Efros.

Non-linear filtering Example: Median filter Replaces pixel value by median value over neighborhood Generates no new gray levels.

Blob detection.

Heechul Han and Kwanghoon Sohn

Trilateral Filtering of Range Images Using Normal Inner Products

Inverse Rendering Shida Beigpour.

CPSC 6040 Computer Graphics Images

Range Image Segmentation for Modeling and Object Detection in Urban Scenes Cecilia Chen & Ioannis Stamos Computer Science Department Graduate Center, Hunter.

Decimation Of Triangle Meshes

CS Computer Graphics II

Nov. 11, Visualization with 3D CG

Math 3360: Mathematical Imaging

The Chinese University of Hong Kong

Fast Bilateral Filtering for the Display of High-Dynamic-Range Images

Lecture 2: Edge detection

Introduction Computer vision is the analysis of digital images

Introduction to Computer Graphics with WebGL

Image filtering Images by Pawan Sinha.

Physics-based simulation for visual computing applications

Image Restoration - Focus on Noise

Histogram Probability distribution of the different grays in an image.

Computing Vertex Normals from Arbitrary Meshes

Digital Visual Effects, Spring 2006 Yung-Yu Chuang 2006/3/8

Image filtering

Edge Detection in Computer Vision

Topic 1 Three related sub-fields Image processing Computer vision

Introduction Computer vision is the analysis of digital images

Image Filtering Readings: Ch 5: 5. 4, 5. 5, 5. 6, , 5

Image Enhancement in the Spatial Domain

Computer Graphics Image processing 紀明德

Presentation transcript:

The Trilateral Filter for High Contrast Images and Meshes Prasun Choudhury and Jack Tumblin Speaker: Di jiantao Feb 28,2008

About the author---Prasun Choudhury Current: Computer Scientist at Adobe Systems Inc. Past: Computer Graphics Research Engineer at Nokia Research Center. Staff software Engineer at Intel Corp. Simulation Software Engineer at Immersion Corp. Education: Northwestern University Indian Institute of Science Jadavpur University RKM Narendrapur

About the author---Jack Tumblin Associate Professor, EECS Department, Computer Science, Northwestern University. Research interests: Computational Photography & Illumination. Computer Vision and Interactive Computer Graphics. High Dynamic Range (HDR) Images and Image Processing. Digital Archives of Visual Appearance for Museum Collections. Human Visual Perception, Psychophysics, and Physiology.

Filter methods: Gaussian Filter * =

Filter methods: Bilateral Filter * =

Gaussian, Bilateral and Trilateral Filter Windows The changes of Trilateral filter: Tilting. S measures its closeness to the plane through I(x). Adaptive neighborhood.

Step 1 of Trilateral Filter for Image Bilateral smooth gradients

Step2 of Trilateral Filter for Image Trilateral smooth image Compute approximate value Compute Filter

Results

Results

Results

Application 1: Contrast Reduction Contrast reduction method based on edge-preserving filters. Base is compressible and Details are incompressible. Compress:

Results of Contrast Reduction

Results of Contrast Reduction

Results of Contrast Reduction

Application 2: Mesh Smoothing A two-step process: Trilateral normal filtering. Bilateral smooth vertex normal. Trilateral vertex filtering.

Signs Definition ---vertex position ---vertex normal ---mesh face ---face normal ---face center point ---bilaterally smoothed vertex normal ---tangent plane pass through

Trilateral normal filter

Trilateral Vertex Filter is the projection of on the plane

Results of Mesh Smoothing Original Model Smoothed Model Noisy Model

Results of Mesh Smoothing

Results of Mesh Smoothing

Thank you!