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Spatial-based Enhancements

Spatial-based Enhancements

Spatial-based Enhancements. Lecture 5 prepared by R. Lathrop 10/99 updated 2/05 ERDAS Field Guide 5th Ed. Ch 5:154-162. Where in the World?. Learning objectives. Remote sensing science concepts Concept of spatial frequency Texture Edge Enhancement/Sharpening Edge Detection/Extraction

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888 views • 65 slides
3-D Computater Vision CSc 83020

3-D Computater Vision CSc 83020

3-D Computater Vision CSc 83020. Revisit filtering (Gaussian and Median) Introduction to edge detection. Linear Filters. Given an image In ( x , y ) generate a new image Out ( x , y ):

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563 views • 50 slides
Digital Image Processing

Digital Image Processing

Digital Image Processing. Image Restoration: Noise Removal. Contents. In this lecture we will look at image restoration techniques used for noise removal What is image restoration? Noise and images Noise models Noise removal using spatial domain filtering Periodic noise

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1.44k views • 46 slides
60-520 Presentation Image Filters

60-520 Presentation Image Filters

60-520 Presentation Image Filters. School of Computer Science University of Windsor November 2003. Outline. Introduction Spatial Filtering Smoothing Sharpening Frequency-Domain Filtering Low pass High pass Summary. Introduction.

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623 views • 46 slides
Introduction

Introduction

Introduction. Computer vision is the analysis of digital images by a computer for such applications as:. Industrial: part localization and inspection, robotics Medical: disease classification, screening, planning Military: autonomous vehicles, tank recognition

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394 views • 35 slides

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