CS 519: Signal & Image Processing Course Overview, Quizzes of Computer Science

An overview of cs 519 – signal & image processing course offered at oregon state university. The course covers digital image processing, prerequisites, assignments, grading, academic dishonesty, and more. Students will learn level operations, algebraic and logical operations, geometric transformations, filtering, sampling, restoration, color processing, and compression. Applications include multimedia, image editing, medical imaging, compression, document processing, and image libraries.

Typology: Quizzes

Pre 2010

Uploaded on 08/30/2009

koofers-user-8x5
koofers-user-8x5 🇺🇸

10 documents

1 / 10

Toggle sidebar

This page cannot be seen from the preview

Don't miss anything!

bg1
1
CS 519 Signal & Image Processing
Introduction
Course Information
Instructor: Eric N. Mortensen ([email protected])
Office: 306 Dearborn Hall
Office Hours: Tuesday 10:00 11:00
Friday 10:00 11:00
Web page: http://engr.oregonstate.edu/classes/cs/cs519/
Mailing list: [email protected]
Required text: Digital Image Processing, Kenneth R. Castleman
Optional text: Digital Image Processing (Second Edition),
Rafael C. Gonzalez and Richard E. Woods
pf3
pf4
pf5
pf8
pf9
pfa

Partial preview of the text

Download CS 519: Signal & Image Processing Course Overview and more Quizzes Computer Science in PDF only on Docsity!

CS 519 – Signal & Image Processing

Introduction

Course Information

Instructor: Eric N. Mortensen ([email protected])

Office: 306 Dearborn Hall

Office Hours: Tuesday 10:00 – 11:

Friday 10:00 – 11:

Web page: http://engr.oregonstate.edu/classes/cs/cs519/

Mailing list: [email protected]

Required text: Digital Image Processing , Kenneth R. Castleman

Optional text: Digital Image Processing (Second Edition) ,

Rafael C. Gonzalez and Richard E. Woods

Prerequisites

  • Programming assignments:

ƒ C++ ƒ Qt (multi-platform windowing and graphical user environment library)

  • Math

ƒ Calculus ƒ Complex numbers/arithmetic ƒ Statistics ƒ Linear system theory ƒ Algebra ƒ Linear algebra

Assignments & Grading

  • Assignments

ƒ Qt & Histograms ƒ Histogram Equalization, Image Rotation, Convolution ƒ Fourier Transform ƒ Filtering, Color Spaces, Compression ƒ Maybe one other

  • Tentative Grading

ƒ Programming projects 50% ƒ Midterm 20% ƒ Final 30%

Quiz

• What color is my shirt?

• What am I holding in my right hand?

• How many people are in this room?

Results: easy for humans,

difficult for computers

What are Signals?

  • Signal: a function carrying information
  • Examples:

ƒ Audio ƒ Radio/Television ƒ Images

Types of Signals: Dimensions

  • Temporal signal: function of time

ƒ f ( t ): voice, music, nerve impulses, radar

  • Spatial signal: function of two (or three) spatial dimensions

ƒ f ( x , y ): images (grayscale, color, multi-spectral) ƒ f ( x , y , z ): medical scans (CT, MRI, PET)

  • Spatio-temporal signal: 2/3-D space, 1-D time

ƒ f ( x , y , t ): video/movies

Why Signals?

  • Communications:

ƒ Modems/Networks/Wireless ƒ Audio

  • Images:

ƒ Restoration/Cleanup ƒ Enhancement ƒ Storage/Retrieval/Searching ƒ Manipulation

Digital Image Processing: Summary

Subclass of signal processing dealing with pictures:

ƒ Signal Æ Function conveying information ƒ Image Æ Signal with (at least) 2 spatial dimensions

  • A representation, resemblance, likeness, etc. ƒ Digital Æ perfect storage, transmission, reproduction
  • General-purpose manipulation
  • Low cost memory and disk space
  • Bandwidth increasing

What You Will Learn

  • Level (brightness) operations
  • Algebraic and logical operations
  • Geometric transformations
  • Filtering (both spatial and frequency-based)
  • Sampling
  • Restoration/Reconstruction
  • Color processing
  • Compression

Applications

  • Multimedia (just look at the web)
  • Image Editing and Manipulation (Photoshop)
  • Medical Imaging (CT, MRI)
  • Compression (PNG, JPEG)
  • Document Processing (OCR)
  • Image Libraries (restoration/cleanup, storage, retrieval)
  • Many More

Relation to Other Fields

  • Image Processing: Transform an image into another representation (image), often as a step to achieving some goal

Image Description

Image Processing

Computer Vision

Computer Graphics

  • Computer Vision: Create a description of the imaged scene
  • Computer Graphics: Create an image of the described scene

Previous/Current Research

  • Object Selection for Image Editing (e.g. Composition)

Future Research

  • Movie Editing:

ƒ Tracking and segmenting objects in a movie ƒ Modeling object boundary edges

  • Image-Based Modeling and Rendering:

ƒ Generate 3-D models of objects from video or multiple images ƒ Render the models with original image texture from new viewpoints under different lighting conditions