Introduction to image processing
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This document outlines the course ESB 4573 - Digital Image Processing. It includes 5 course learning outcomes focusing on image sampling, quantization, enhancement techniques, spatial filtering for noise removal, edge detection, color processing, and compression methods. Assessment includes a final exam worth 50% and two tests and assignments making up the remaining 50%. Classes will be held on Tuesdays and Wednesdays. Examples of digital image processing applications discussed are CT scans, ultrasound images, x-rays, light microscopy, and reasons it is useful include supporting visual communication, inspection, diagnosis, entertainment, record keeping, and security.
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- 1. ESB 4573 DIGITAL IMAGE PROCESSING BY HESHALINI RAJAGOPAL
- 2. Lecture 1 Introduction to Digital Image Processing
- 3. COURSE LEARNING OUTCOMES (CLOs) CLO1: Describe various types of images and basic concept of image sampling and quantization. CLO2: Comprehend and Apply various image enhancement techniques such as arithematic histogram strecthing and equalization, threshold techniques using Matlab. CLO3: Choose and Apply apppropriate spatial filtering method to denoise the images distorted with various types of noises. CLO4: Develop Matlab codes for edge detection and edge enhancement to image. CLO5: Apply colour processing on image and choose appropriate image compression method.
- 4. Course Assessment • Final Exam = 50 % • Test (2) = 30 % • Assignments (2) = 20 % Total = 100 %
- 5. Classes and Tests • Classes – Tuesday (4PM-5PM) – Wednesday (9AM-11AM) • Tests – Test 1:Week 5/6 – Test 2: Week 11
- 6. Digital Image and Digital Image Processing • Image – A two-dimensional signal that can be observed by human visual system • Digital image – Representation of images by sampling in time and space. • Digital image processing – perform digital signal processing operations on digital images
- 7. Examples of DIP: CT: Computer Tomography • http://www.nlm.nih.gov/research/vi sible/image/head.jpg • Section through Visible Human Male - head, including cerebellum, cerebral cortex, brainstem, nasal passages (from Head subset) • This is an example of the “visible human project” sponsored by NIH • DIP techniques applicable: – Enhancement – Segmentation
- 8. Ultrasound Image • Profiles of a fetus at 4 months, the face is about 4cm long • Ultra sound image is another imaging modality • The fetal arm with the major arteries (radial and ulnar) clearly delineated. http://www.parenthood.com/us.html
- 11. Figure 1.7 X-Ray images. (a) Chest X-ray. (b) Aortic angiogram. (c) Head CT. (d) Circuit boards. (e) Cygnus Loop.
- 13. (c) 2002-2004 by Yu Hen Hu Figure 1.9 Light microscopy images. (a) Taxol (anticancer agent), magnified 250X, (b) Cholesterol, 40X (c) microprocessor 60X. (d) Nickel oxide thin film, 600 X. (e) Surface of audio CD 1750 X. (f) Organic superconductor 450 X.
- 14. Why DIP? • One picture worth 1000 words! • Support visual communication • Facilitate inspection, diagnosis of complex systems – Human body – Manufacturing • Entertainment • Keep record, history • Managing multimedia information • Security, – monitoring, – watermarking, etc
- 15. (c) 2002-2004 by Yu Hen Hu