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Dive into Digital Image Processing: Fundamentals and Applications

Explore the mathematical representation of digital images, sampling, quantization, preprocessing, and more in this comprehensive course. Understand the basics of image acquisition, recognition, and interpretation while delving into human eye anatomy and perception. Get hands-on with MATLAB IP Toolbox in pre-lab tasks to enhance your skills.

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Dive into Digital Image Processing: Fundamentals and Applications

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  1. Digital Image ProcessingECE.09.452/ECE.09.552Fall 2007 Lecture 1September 10, 2007 Shreekanth Mandayam ECE Department Rowan University http://engineering.rowan.edu/~shreek/fall07/dip/

  2. http://www.apple.com/iphone/

  3. Hurricane Katrina regional imagery, 2005.08.29 at 1215Z. Centerpoint Latitude: 31:10:43N Longitude: 88:50:53W.

  4. ABA E-13B Font

  5. Biometrics

  6. Plan • What is an image? • Mathematical representation of monochromatic images • What is a digital image? • Digital image processing • Fundamental steps • Why do we need this? • Course logistics • Self-Assessment Test • Sampling & Quantization • Image Preprocessing • Pre-Lab 1

  7. column f(x, y) row y x Images Sample Quantize

  8. Digital Image y x Gray Level f(x,y)

  9. M B R W Y C G Color Images Mixtures of Light: Additive Primaries

  10. B B G G R+G+B R+G+B R R B G R+G+B R B G R+G+B B R G R+G+B R B G R+G+B R

  11. RGB Color Space

  12. Fundamental Steps Representation & Description Preprocessing Segmentation Knowledge Base Problem Domain Image Acquisition Recognition & Interpretation Result

  13. The Human Eye Sagittal section of adult human eye Section of human retina http://webvision.med.utah.edu/anatomy.html

  14. Perceived Brightness

  15. Perceived Contrast

  16. Optical Illusions

  17. DIP: Details

  18. DIP: Course Logistics http://engineering.rowan.edu/~shreek/fall07/dip/

  19. Sampling & Quantization • Sampling demos/demo1sampling_and_quantization/demo_sampling.m • Quantization demos/demo1sampling_and_quantization/demo_quant.m

  20. Image Preprocessing Restoration Enhancement • Inverse filtering • Wiener filtering Spectral Domain Spatial Domain • Filtering • >>fft2/ifft2 • >>fftshift • Point Processing • >>imadjust • >>histeq • Spatial filtering • >>filter2

  21. Point Processing(Intensity Transformation) s(x,y) = T{ r(x,y)} Transformed Gray Level Original Gray Level Transformation Function >>imadjdemo >>imadjust

  22. Pre-Lab 1: Intro to Matlab IP Toolbox http://engineering.rowan.edu/~shreek/fall07/dip/ipintro.html

  23. Summary

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