'Image restoration' presentation slideshows

Digital Image Processing Image Restoration Dr. Ziya Telatar Ankara University

Digital Image Processing Image Restoration Dr. Ziya Telatar Ankara University. D igital I mage P rocessing : Details. Image Preprocessing. Restoration. Enhancement. Inverse filtering Blind Deconvolution Wiener filtering Cepstrum Least Squares Regularization Tech. ............

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The Art of Digital Image processing

The Art of Digital Image processing. C. S. Tong Department of Mathematics Hong Kong Baptist University. Is the left center circle bigger?. No, they're both the same size. It's a spiral, right?. No, these are a bunch of independent circles.

796 views • 69 slides

Image Restoration

1.19k views • 62 slides

Image Restoration

Image Restoration. 1. Introduction. Degradations Noises (Dot/Pattern) Illumination Imperfections (Brightness /Contrast) Color Imperfections Blurring. Image Blur Out-of-Focus Blur Aberrations in the optical systems Motion Blur Atmospheric Turbulence Blur.

740 views • 60 slides

Achievement

Achievement. Visual. RENDERING. Making clipart in motion. LOW RESOLUTION TO HIGH RESOLUTION. HIGH RESOLUTION. LOW RESOLUTION. HIGH RESOLUTION. LOW RESOLUTION. LOW RESOLUTION. HIGH RESOLUTION. IMAGE RESTORATION. MAKING 3D FOR CLIENTS. DESIGNING. PACKAGING. DANGLER.

757 views • 54 slides

Chapter 5 Image Restoration

Chapter 5 Image Restoration. Chapter 5 Image Restoration. Chapter 5 Image Restoration. Chapter 5 Image Restoration. Chapter 5 Image Restoration. Chapter 5 Image Restoration. Chapter 5 Image Restoration. Chapter 5 Image Restoration. Chapter 5 Image Restoration. Chapter 5

998 views • 40 slides

Fundamentals of Digital Image Processing

Fundamentals of Digital Image Processing. Dr. Hiren D. Joshi Dept. of Computer Science Rollwala Computer Centre Gujarat University. Introduction. Digital Image processing methods were introduced in 1920.

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BAE 790I / BMME 231 Fundamentals of Image Processing Class 18

BAE 790I / BMME 231 Fundamentals of Image Processing Class 18. Restoration Filtering Inverse Filters: Properties Wiener Filters MSE Properties. Image Restoration. Objective: To quantitatively estimate the true image from its degraded measurement. System H. Restoration process. +. g.

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Loopy belief propagation and probabilistic image processing

Loopy belief propagation and probabilistic image processing. K. Tanaka (Tohoku University, Japan) J. Inoue (Hokkaido University, Japan) D. M. Titterington (University of Glasgow, UK). Image Processing and Magnetic Material. Regular lattice consisting of a lot of nodes.

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Image Processing: Linear Filtering

Image Processing: Linear Filtering. Modifikasi dari: Prof. Zhou Wang, Texas Univ., 2006. Linear Filtering. Spatial Domain Linear Filtering Frequency (2D-DFT) Domain Filtering Linear Image Restoration. Image Restoration. Blur. From Prof. Xin Li. out-of-focus blur. motion blur.

548 views • 24 slides

Probabilistic image processing based on the Q -Ising model by means of the mean-field method and loopy belief propagati

Probabilistic image processing based on the Q -Ising model by means of the mean-field method and loopy belief propagation. Kazuyuki Tanaka Graduate School of Information Sciences, Tohoku University, Japan kazu@statp.is.tohoku.ac.jp http://www.statp.is.tohoku.ac.jp/~kazu/ and

399 views • 23 slides

Image Processing

Image Processing. Image Restoration Part 1. What is Image Restoration?. Image restoration attempts to restore images that have been degraded by using a prior knowledge of the degradation phenomenon. Identify the degradation process and attempt to reverse it

634 views • 20 slides

Real-time secure technology to transmit and receive e-code

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Topic 9 - Image Restoration

Topic 9 - Image Restoration. Department of Physics and Astronomy. DIGITAL IMAGE PROCESSING Course 3624. Professor Bob Warwick. Restoring a Blurred Image.

355 views • 16 slides

Figure 8-1 (p. 491) Adaptive channel equalizer.

Figure 8-1 (p. 491) Adaptive channel equalizer. Figure 8-2 (p. 493) Equalizer performance with the LMS algorithm. Figure 8-3 (p. 493) Equalizer performance with the RLS algorithm. Figure 8-4 (p. 500) Weight for conventional least-squares cost function.

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Image Processing: Critical to Hubble Discoveries

Image Processing: Critical to Hubble Discoveries. Presented by Chris Lavin and Lucas Divine. The Hubble Space Telescope (HST). HST program run by Space Telescope Science Institute for NASA Quick Facts: Deployed 1990 Orbits Earth in 87 minutes 24.5 Thousand Pounds

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Digital Image processing Homework 4

Digital Image processing Homework 4. Jheng-Ping Lin Visual Communications Lab Department of Communication Engineering National Central University Jhongli,Taiwan December 11, 2008. Image Restoration for Image Blurring. Deblurring Filter. Restoration. Blurred Image.

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ECE 533 Digital Image Processing

ECE 533 Digital Image Processing. Outline. Course homepage: http://www.cae.wisc.edu/~ece533/ Course descriptions Outlines Course conduct. Goals: Understand 2D signal processing theory Familiar with basic image processing techniques: filtering, restoration, coding

461 views • 9 slides

Research Idea

Research Idea. Lei Rao Feb. 7th, 2009. Basic Idea of Image Restoration. g (x, y). Degradation Function H. Restoration Filter (s). f (x, y). +. f* (x, y). Noise n (x, y). Question: How to reconstruct the original image f (x, y) from the observation g (x, y)?

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158 views • 4 slides