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Introduction to Digital Image Processing. February 25, 2003. Shreekanth Mandayam ECE Department Rowan University http://engineering.rowan.edu/~shreek/spring03/cc/. Hurricane Fran, TIME Magazine, Sept. 16, 1996 Picture Taken by: GOES-8, NASA GODDARD SPACE FLIGHT CENTER. ABA E-13B Font.
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Introduction to Digital Image Processing February 25, 2003 Shreekanth Mandayam ECE Department Rowan University http://engineering.rowan.edu/~shreek/spring03/cc/
Hurricane Fran, TIME Magazine, Sept. 16, 1996 Picture Taken by: GOES-8, NASA GODDARD SPACE FLIGHT CENTER
Module Overview • Lecture 1 • Digital Image Fundamentals • Digital Image Enhancement • Lecture 2 • Digital Image Segmentation • Digital Image Compression
Lecture 1 Digital Image Fundamentals
Lecture 1: 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? • Sampling & Quantization • Image Preprocessing
column f(x, y) row y x Images Sample Quantize
Monochromatic Digital Image y x Gray Level f(x,y)
M B R W Y C G Color Images Mixtures of Light: Additive Primaries
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
Fundamental Steps* Preprocessing (Enhancement & Restoration) Representation & Description Segmentation Knowledge Base Problem Domain Image Acquisition Recognition & Interpretation Result *Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, Addison-Wesley, 1992
Sampling & Quantization • Sampling demos/demo1sampling_and_quantization/demo_sampling.m • Quantization demos/demo1sampling_and_quantization/demo_quant.m Digital Image Processing Course Nos. 0909-452-01 (Senior Elective) and 0909-552-01 (Graduate)Fall 2003 Previous Offering: http://engineering.rowan.edu/~shreek/fall01/dip/
Image Preprocessing Restoration Enhancement • Inverse filtering • Wiener filtering Spectral Domain Spatial Domain • Filtering • >>fft2/ifft2 • >>fftshift • Point Processing • >>imadjust • >>histeq • Spatial filtering • >>filter2
Point Processing(Intensity Transformation) s(x,y) = T{ r(x,y)} Transformed Gray Level Original Gray Level Transformation Function >>imadjdemo >>imadjust
Point Processing • Pixel Operations • Point processing • Histogram equalization • Connectivity individual pixels all pixels neighboring pixels
L-1 0 L-1 0 Point Processing L-1 s2 s g s s1 0 r r r1 r2 L-1 0 >>imadjdemo >>imadjust
Image Histogram >>imadjdemo >>imhist
Histogram Equalization(Balancing) >>imadjdemo >>histeq
Summary Digital Image Processing Course Nos. 0909-452-01 (Senior Elective) and 0909-552-01 (Graduate)Fall 2003 Previous Offering: http://engineering.rowan.edu/~shreek/fall01/dip/ • Next Tuesday: Lecture 2 • Digital Image Segmentation • Digital Image Compression