'Bilinear interpolation' presentation slideshows

Java 101: Imaging & Java

Java 101: Imaging & Java. Ryan Cuprak. Java Media APIs. Java2D Java Advanced Imaging (JAI) Java Media Framework (JMF) Java3D. Agenda. Digital imaging basics Java Imaging Foundation Image I/O Java Advanced Imaging. Java Imaging Foundation. Java Imaging Foundation.

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INCA Nowcasting system

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DIGITAL IMAGE CORRELATION

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ELE 488 Fall 2006 Image Processing and Transmission (10-12-06)

10/12/06. ELE 488 Fall 2006 Image Processing and Transmission (10-12-06). Re-sampling and Re-sizing 1D ? 2D, sinc interpolation nearest neighbor, bilinear, bicubic, . . . Geometric Transformation translation rotation scaling Affine.

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Parallel ODETLAP for Terrain Compression and Reconstruction

Parallel ODETLAP for Terrain Compression and Reconstruction. Jared Stookey Zhongyi Xie W. Randolph Franklin. Dan Tracy Barbara Cutler Marcus V. A. Andrade. Outline. Quick Overview of our research ODETLAP (Non-Patch) Motivation for Parallelization Our Approach MPI Implementation

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Parallel ODETLAP for Terrain Compression and Reconstruction

Parallel ODETLAP for Terrain Compression and Reconstruction. Jared Stookey Zhongyi Xie W. Randolph Franklin. Dan Tracy Barbara Cutler Marcus V. A. Andrade. Outline. Quick Overview of our research ODETLAP (Non-Patch) Motivation for Parallelization Our Approach MPI Implementation

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Computer Graphics

Lecture 7 Texture Mapping, Bump-mapping, Transparency. Computer Graphics. Today. Texture mapping Anti-aliasing techniques Bump mapping Transparency. Aliasing . Happens when T he camera is zoomed too much into the textured surface (magnification) ?

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Interpolation

Interpolation. Prof. Noah Snavely CS1114 http://www.cs.cornell.edu/courses/cs1114. Administrivia. Assignment 3 due tomorrow by 5pm Please sign up for a demo slot Assignment 4 will be posted tomorrow evening Quiz 3 next Thursday. Today: back to images. This photo is too small:

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Interpolation

Interpolation. Prof. Noah Snavely CS1114 http://www.cs.cornell.edu/courses/cs1114. Administrivia. Assignment 3 due tomorrow by 5pm Please sign up for a demo slot Assignment 4 will be posted tomorrow evening Quiz 3 next Thursday. Today: back to images. This photo is too small:

464 views • 33 slides

Geostatistics

Geostatistics. Mike Goodchild. Spatial interpolation. A field variable is interval/ratio z = f ( x , y ) sampled at a set of points How to estimate/guess the value of the field at other points?. Characteristics of interpolated surfaces. Representation raster, isolines, TIN Form

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Chapter 6: Image Geometry 6.1 Interpolation of Data

Chapter 6: Image Geometry 6.1 Interpolation of Data. Suppose we have a collection of four values that we wish to enlarge to eight. The a and b of the linear function can be solved by Then we can obtain the linear function. (continuous). 6.1 Interpolation of Data.

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Real-Time Volume Graphics [03] GPU-Based Volume Rendering

Real-Time Volume Graphics [03] GPU-Based Volume Rendering. Volume Rendering. Image order approach:. Data Set. Image Plane. Eye. For each pixel { calculate color of the pixel }. Volume Rendering. Image order approach:. Object order approach:. Data Set. Image Plane. Eye.

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Arithmetic and Geometric Transformations (Chapter 2)

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Sampling and Pyramids

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Arithmetic and Geometric Transformations

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Distributed Image Coding with Improved Estimation of Disparity and Noise

Distributed Image Coding with Improved Estimation of Disparity and Noise. David Chen Stanford University EE398B Final Project. Outline. Existing distributed image coder Interpolation of disparity field to pixel resolution Edge-based noise estimation Shape-based disparity estimation

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Bayer Color Filter Array Demosaicing

Bayer Color Filter Array Demosaicing. EE362/Psyc221 Yu-Yao Chang. Outline. Introduction Algorithms Result Conclusion. EE362/Psyc221 Yu-Yao Chang. Introduction. Why demosaicing?. EE362/Psyc221 Yu-Yao Chang. Introduction. Bayer Color Filter Array. EE362/Psyc221 Yu-Yao Chang.

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EE368b Project

EE368b Project. Evaluation of search strategies for block matching Marcus Isaksson Joakim Jalden. Evaluation of search strategies for block matching. Joakim Jald?n and Marcus Isaksson. Block matching. Main goals of a block matching scheme Find best match for any given block

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An efficient method of license plate location

An efficient method of license plate location. Pattern Recognition Letters 26 (2005) 2431-2438 Journal of Electronic Imaging 11(4), 507-516 (October 2002) . Presented by - Waseem Khatri. Objective :. To efficiently locate a license plate in an image Motivation:

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Image Interpolation

Image Interpolation. Signals and image processing by computer Winter 2012-13 Yael Erez. Image Interpolation. Sampled Image: Reconstructed image by interpolation:. Image Interpolation. Separable Interpolation Kernels Shannon Kernel

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