'Median filter' diaporamas de présentation

CSCE 641 Computer Graphics: Image Processing

CSCE 641 Computer Graphics: Image Processing. Jinxiang Chai. Review. 2D Fourier Transform Nyquist sampling theory - Sampling Rate ? 2 * max frequency in the signal Antialiasing - prefiltering Gaussian pyramid - Mipmap. Review. 2D Fourier Transform Nyquist sampling theory

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Predspracovanie obrazu

Predspracovanie obrazu. Gonzales, Woods: Digital Image Processing 2002 kapitola : Image restoration Sonka , Hlavac , Boyle : Image Processing , Analysis and Machine vision , kapitola: Image pre-processing Szeliski : Computer Vision : Algorithms and Applications

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CS448f: Image Processing For Photography and Vision

CS448f: Image Processing For Photography and Vision. Fast Filtering Continued. Filtering by Resampling. This looks like we just zoomed a small image Can we filter by downsampling then upsampling ?. Filtering by Resampling. Filtering by Resampling. Downsampled with rect (averaging down)

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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.

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Image Restoration

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Image Processing in SIGGRAPH 06

Image Processing in SIGGRAPH 06. Speaker: Qianqian Hu Date: March 31, 2006. Outlines. Fast Median and Bilateral Filtering Ben Weiss ( Shell & Slate Software ) Hybrid Images

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Edge Preserving Smoothing Techniques

Edge Preserving Smoothing Techniques. Prof. PhD. Vasile Gui Polytechnic University of Timisoara. Content. Introduction Brief review of linear operators Linear image smoothing techniques Nonlinear image smoothing techniques. Introduction. Why do we need image smoothing?

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Chapter 2. ?????????. ?????? (Digital Image Processing). ? ????????. ??????? ????? ???????. ? Filter ??. ? ?????. ? ?????? (Data compression ?. ? ???? ? ?. Digital Image Fundamentals. Image Enhancement in the Spatial Domain. Using the negative transformation. ??? (Spatial domain).

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Instructor: Juyong Zhang juyong@ustc stafftc/~juyong

Image Processing. The Median Filter. Instructor: Juyong Zhang juyong@ustc.edu.cn http://staff.ustc.edu.cn/~juyong. The Median Filter. Returns the median value of the pixels in a neighborhood Is non- linear

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MegaMeet 2009 Atlanta GA

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Mean and Median Filters

Mean and Median Filters. ???????? ???????? ??? E9406011. Outline. Introduction Mean Filter Median Filter Summary Demo. Introduction. ???????. ????????? ??? (frequency domain) ????????? ?? ( ???? , ?? ) ??????????

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Image Restoration

Image Restoration. Introduction. Image restoration concerns the removal or reduction of image degradation that have occurred during the acquisition of the image Degradation due to noise, optical effects Using neighborhood operations, frequency domain processes. Model. Spatial domain

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Image Analysis

Image Analysis. Preprocessing Arithmetic and Logic Operations Spatial Filters Image Quantization. Arithmetic and Logic Operations. Arithmetic and logic operations are often applied a preprocessing steps in image analysis in order to combine images in various way.

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Instructor: Lichuan Gui lichuan-gui@uiowa lcgui

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Image Analysis

Image Analysis. Image Restoration. Image Restoration. Image enhancement tries to improve subjective image quality. Image restoration tries to recover the original image. Noise Models. Noise may arise during image due to sensors, digitization, transmission, etc.

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Computer Vision System for Tracking Players in Sports Games

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Solar Feature Catalogues

Solar Feature Catalogues. S Zharkov, V V Zharkova, S S Ipson, A.Benkhalil, N.Fuller, J. Aboudarham. EGSO SFC Specifications. Purpose Provide comprehensive information about: (a) features detected on a date; (b) provide a cropped image library;

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Interpolation

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Digital Image Forensics

Digital Image Forensics. CS 365 By:- - Abhijit Sarang - Pankaj Jindal. Which of them are digitally manipulated?. How can we know?.

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PROGRESS PRESENTATION

Assignment 0X (dd/mm/yyyy) JohnSmith, JohnSmith, JohnSmith, JohnSmith, JohnSmith. PROGRESS PRESENTATION. Assignment description. Color Depolarization of super-pixel artifacts Multifiltering of spectral Gaussians Decoloration of traffic lipids.

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