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lec01_filter - CS6670:ComputerVision NoahSnavely Lecture1:...

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Lecture 1: Images and image filtering CS6670: Computer Vision Noah Snavely Hybrid Images, Oliva et al., http://cvcl.mit.edu/hybridimage.htm
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CS6670: Computer Vision Noah Snavely Hybrid Images, Oliva et al., http://cvcl.mit.edu/hybridimage.htm Lecture 1: Images and image filtering
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Reading Szeliski, Chapter 3.1 3.2
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What is an image? Digital Camera The Eye Source: A. Efros We’ll focus on these in this class (More on this process later)
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What is an image? A grid of intensity values (common to use one byte per value: 0 = black, 255 = white) = 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 20 0 255 255 255 255 255 255 255 255 255 255 75 75 75 255 255 255 255 255 255 255 255 75 95 95 75 255 255 255 255 255 255 255 255 96 127 145 175 255 255 255 255 255 255 255 255 127 145 175 175 175 255 255 255 255 255 255 255 127 145 200 200 175 175 95 255 255 255 255 255 127 145 200 200 175 175 95 47 255 255 255 255 127 145 145 175 127 127 95 47 255 255 255 255 74 127 127 127 95 95 95 47 255 255 255 255 255 74 74 74 74 74 74 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255
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We can think of a (grayscale) image as a function , f , from R 2 to R: f ( x,y ) gives the intensity at position ( x,y ) A digital image is a discrete ( sampled , quantized ) version of this function What is an image?
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lec01_filter - CS6670:ComputerVision NoahSnavely Lecture1:...

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