狠狠撸

狠狠撸Share a Scribd company logo

Lecture 1 introduction

?Download as PPT, PDF?
?
Faisel Al-Jafari
Faisel Al-Jafari

This document provides an overview of a lecture on digital image processing. It discusses grading criteria which includes article reading, homework, exams and practical work. Example article reading and project topics are listed covering areas like medical imaging and object recognition. Key stages of digital image processing are introduced including image acquisition, restoration, enhancement, representation and compression. References and an outline of topics to be covered are also provided such as the definition of digital images, sources of error and the history and applications of digital image processing.

1 of 18
Lecture 1 Digital Image Processing: Introduction Lecturer: Dr. Faisel Ghazee Mohammed Email: faisel@scbaghdad.edu.iq faiselgm73@gmail.com 2010-2011 All rights reserved
Grading Article Reading and Presentation: 10% Homework: 10% Exam: 30% Practical: 50% Total: 100% Extra Credits: 50%. If the method and experimental results of your project achieve the state of the art, you will earn the extra 50% credits. Introduction to the course
Article Reading and Projects 1. Medical image analysis (MRI/PET/CT/X-ray tumor detection/classification) 2. Face, fingerprint, and other object recognition 3. Image and/or video compression 4. Image segmentation and/or denoising 5. Digital image/video watermarking/steganography and detection 6. Whatever you’re interested … Introduction to the course
? Evaluation of article reading and project – Report ?Article reading — Submit a survey of the articles you read and the list of the articles ?Project — Submit an article including introduction, methods, experiments, results, and conclusions — Submit the project code, the readme document, and some testing samples (images, videos, etc.) for validation – Presentation Introduction to the course
? Journals: — IEEE T IMAGE PROCESSING — IEEE T MEDICAL IMAGING — INTL J COMP. VISION — IEEE T PATTERN ANALYSIS MACHINE INTELLIGENCE — PATTERN RECOGNITION — COMP. VISION AND IMAGE UNDERSTANDING — IMAGE AND VISION COMPUTING … … ? Conferences: — CVPR: Comp. Vision and Pattern Recognition — ICCV: Intl Conf on Computer Vision — ACM Multimedia — ICIP — SPIE — ECCV: European Conf on Computer Vision — CAIP: Intl Conf on Comp. Analysis of Images and Patterns … … Journals & Conferences in Image Processing
References “Digital Image Processing”, Rafael C. Gonzalez & Richard E. Woods, Addison-Wesley, 2002 Much of the material that follows is taken from this book “IMAGE PROCESSING AND PATTERN RECOGNITION: Fundamentals and Techniques”, FRANK Y. SHIH Published by John Wiley & Sons, Inc., Hoboken, New Jersey.2010
DIP: Topics
Image Preprocessing Enhancement Restoration Spatial Domain Spectral Domain Point Processing Spatial filtering Filtering ? Inverse filtering ? Wiener filtering
Contents This lecture will cover: 1. What is a digital image? 2. What is digital image processing? 3. History of digital image processing 4. State of the art examples of digital image processing 5. Key stages in digital image processing
A digital image is a representation of a two-dimensional image as a finite set of digital values, called picture elements or pixels 1-What is a Digital Image?
Image Resolution 1. Intensity resolution – Each pixel has only “Depth” bits for colors/intensities 1. Spatial resolution – Image has only “Width” x “Height” pixels 1. Temporal resolution – Monitor refreshes images at only “Rate” Hz Width x Height Depth Rate NTSC 640 x 480 8 30 Workstation 1280 x 1024 24 75 Film 3000 x 2000 12 24 Laser Printer 6600 x 5100 1 - Typical Resolutions
Sources of Error 1. Intensity quantization – Not enough intensity resolution 1. Spatial aliasing – Not enough spatial resolution 1. Temporal aliasing – Not enough temporal resolution E: denote to error I(x,y): denote to original pixel value P(x,y): denote to Processed pixel value
Pixel values typically represent gray levels, colours, heights, opacities etc Remember digitization implies that a digital image is an approximation of a real scene 1 pixel 1-What is a Digital Image? Pixel : The elements of a digital image
Common image formats include: –1 sample per point (B&W or Grayscale) –3 samples per point (Red, Green, and Blue) –4 samples per point (Red, Green, Blue, and “Alpha”, For most of this course we will focus on grey-scale images 1-What is a Digital Image?
Vision, Image Processing and Visualization REAL WORLD IMAGE SCENE DESCRIPTION Image Processing Computer Graphics/ Visualization Computer Vision Photography
Low Level Process Input: Image Output: Image Examples: Noise removal, image sharpening Mid Level Process Input: Image Output: Attributes Examples: Object recognition, segmentation High Level Process Input: Attributes Output: Understanding Examples: Scene understanding, autonomous navigation process digital images by means of computer, it covers low-, mid-, and high-level processes low-level: inputs and outputs are images mid-level: outputs are attributes extracted from input images high-level: an ensemble of recognition of individual objects 2-What is a Digital Image Processing?
Image Acquisition Image Restoration Morphological Processing Segmentation Representation & Description Image Enhancement Object Recognition Problem Domain Colour Image Processing Image Compression 5-Key Stages in Digital Image Processing
END Of Lecture 1

More Related Content

Lecture 1 introduction

  • 1. Lecture 1 Digital Image Processing: Introduction Lecturer: Dr. Faisel Ghazee Mohammed Email: faisel@scbaghdad.edu.iq faiselgm73@gmail.com 2010-2011 All rights reserved
  • 2. Grading Article Reading and Presentation: 10% Homework: 10% Exam: 30% Practical: 50% Total: 100% Extra Credits: 50%. If the method and experimental results of your project achieve the state of the art, you will earn the extra 50% credits. Introduction to the course
  • 3. Article Reading and Projects 1. Medical image analysis (MRI/PET/CT/X-ray tumor detection/classification) 2. Face, fingerprint, and other object recognition 3. Image and/or video compression 4. Image segmentation and/or denoising 5. Digital image/video watermarking/steganography and detection 6. Whatever you’re interested … Introduction to the course
  • 4. ? Evaluation of article reading and project – Report ?Article reading — Submit a survey of the articles you read and the list of the articles ?Project — Submit an article including introduction, methods, experiments, results, and conclusions — Submit the project code, the readme document, and some testing samples (images, videos, etc.) for validation – Presentation Introduction to the course
  • 5. ? Journals: — IEEE T IMAGE PROCESSING — IEEE T MEDICAL IMAGING — INTL J COMP. VISION — IEEE T PATTERN ANALYSIS MACHINE INTELLIGENCE — PATTERN RECOGNITION — COMP. VISION AND IMAGE UNDERSTANDING — IMAGE AND VISION COMPUTING … … ? Conferences: — CVPR: Comp. Vision and Pattern Recognition — ICCV: Intl Conf on Computer Vision — ACM Multimedia — ICIP — SPIE — ECCV: European Conf on Computer Vision — CAIP: Intl Conf on Comp. Analysis of Images and Patterns … … Journals & Conferences in Image Processing
  • 6. References “Digital Image Processing”, Rafael C. Gonzalez & Richard E. Woods, Addison-Wesley, 2002 Much of the material that follows is taken from this book “IMAGE PROCESSING AND PATTERN RECOGNITION: Fundamentals and Techniques”, FRANK Y. SHIH Published by John Wiley & Sons, Inc., Hoboken, New Jersey.2010
  • 8. Image Preprocessing Enhancement Restoration Spatial Domain Spectral Domain Point Processing Spatial filtering Filtering ? Inverse filtering ? Wiener filtering
  • 9. Contents This lecture will cover: 1. What is a digital image? 2. What is digital image processing? 3. History of digital image processing 4. State of the art examples of digital image processing 5. Key stages in digital image processing
  • 10. A digital image is a representation of a two-dimensional image as a finite set of digital values, called picture elements or pixels 1-What is a Digital Image?
  • 11. Image Resolution 1. Intensity resolution – Each pixel has only “Depth” bits for colors/intensities 1. Spatial resolution – Image has only “Width” x “Height” pixels 1. Temporal resolution – Monitor refreshes images at only “Rate” Hz Width x Height Depth Rate NTSC 640 x 480 8 30 Workstation 1280 x 1024 24 75 Film 3000 x 2000 12 24 Laser Printer 6600 x 5100 1 - Typical Resolutions
  • 12. Sources of Error 1. Intensity quantization – Not enough intensity resolution 1. Spatial aliasing – Not enough spatial resolution 1. Temporal aliasing – Not enough temporal resolution E: denote to error I(x,y): denote to original pixel value P(x,y): denote to Processed pixel value
  • 13. Pixel values typically represent gray levels, colours, heights, opacities etc Remember digitization implies that a digital image is an approximation of a real scene 1 pixel 1-What is a Digital Image? Pixel : The elements of a digital image
  • 14. Common image formats include: –1 sample per point (B&W or Grayscale) –3 samples per point (Red, Green, and Blue) –4 samples per point (Red, Green, Blue, and “Alpha”, For most of this course we will focus on grey-scale images 1-What is a Digital Image?
  • 15. Vision, Image Processing and Visualization REAL WORLD IMAGE SCENE DESCRIPTION Image Processing Computer Graphics/ Visualization Computer Vision Photography
  • 16. Low Level Process Input: Image Output: Image Examples: Noise removal, image sharpening Mid Level Process Input: Image Output: Attributes Examples: Object recognition, segmentation High Level Process Input: Attributes Output: Understanding Examples: Scene understanding, autonomous navigation process digital images by means of computer, it covers low-, mid-, and high-level processes low-level: inputs and outputs are images mid-level: outputs are attributes extracted from input images high-level: an ensemble of recognition of individual objects 2-What is a Digital Image Processing?

Editor's Notes

  1. Real world is continuous – an image is simply a digital approximation of this.
  2. Give the analogy of the character recognition system. Low Level: Cleaning up the image of some text Mid level: Segmenting the text from the background and recognising individual characters High level: Understanding what the text says