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Digital Image Processing

Explore the mathematical representation of monochromatic images, digital image processing steps, and the importance of image processing in problem domains. This guide covers image acquisition, preprocessing, segmentation, and enhancement techniques, such as inverse filtering, Wiener filtering, spatial filtering, and point processing using intensity transformations.

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Digital Image Processing

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  1. Digital Image Processing

  2. 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?

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

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

  5. Fundamental Steps* Representation & Description Preprocessing Segmentation Knowledge Base Problem Domain Image Acquisition Recognition & Interpretation Result *Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, Addison-Wesley, 1992

  6. DIP: Details

  7. DIP: Course Logistics http://faculty.petra.ac.id/resmana

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

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

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