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Exercise 1 - Poisson

Exercise 1 - Poisson. Image completion using Discrete Poisson Linear Systems. Exercise 1 - Poisson. if I x,y is not black P x,y = I x,y else 4P x,y - P x-1,y - P x+1,y - P x,y-1 - P x,y+1 = 0 (m)x(n) image ( m·n )x( m·n ) linear system. Resolution: 480x320

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Exercise 1 - Poisson

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  1. Exercise 1 - Poisson • Image completion using Discrete Poisson Linear Systems

  2. Exercise 1 - Poisson if Ix,y is not blackPx,y = Ix,yelse4Px,y - Px-1,y - Px+1,y - Px,y-1 - Px,y+1 = 0 (m)x(n) image (m·n)x(m·n) linear system Resolution: 480x320 Linear System: 153600x 153600 Resolution: 576x300 Linear System: 172800x172800

  3. Exercise 1 - Poisson Image Cloning

  4. Representing an image Using a 1D array to represent a 2D image.index(x,y) = y*numOfColumns + x. This basically serializes the image row after row. Coordinate (0,0) is always the upper left corner.The y coordinates increment going down, as opposed to normal Cartesian coordinates.

  5. Representing Color BufferedImageimg = ...int c = img.getRGB(x, y); // c == 16597993 ??? A pixel is represented by 3 values for the 3 color channels.Each color value is a number in the range [0,255].Fits a single unsigned byte.To extract the separate values, use bit operations16597993 = 0x00FD43E9blue E9=233green 43=67red FD=253

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