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CS 445 / CS 645

CS 445 / CS 645. Antialiasing. What is a pixel?. A pixel is not… A box A disk A teeny tiny little light A pixel is a point It has no dimension It occupies no area It cannot be seen It can have a coordinate. A pixel is more than a point, it is a sample. Samples.

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CS 445 / CS 645

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  1. CS 445 / CS 645 Antialiasing

  2. What is a pixel? • A pixel is not… • A box • A disk • A teeny tiny little light • A pixel is a point • It has no dimension • It occupies no area • It cannot be seen • It can have a coordinate A pixel is more than a point, it is a sample

  3. Samples • Most things in the real world are continuous • Everything in a computer is discrete • The process of mapping a continuous function to a discrete one is called sampling • The process of mapping a continuous variable to a discrete one is called quantization • Rendering an image requires sampling and quantization

  4. Samples

  5. Samples

  6. Line Segments • We tried to sample a line segment so it would map to a 2D raster display • We quantized the pixel values to 0 or 1 • We saw stair steps, or jaggies

  7. Line Segments • Instead, quantize to many shades • But what sampling algorithm is used?

  8. Area Sampling • Shade pixels according to the area covered by thickened line • This is unweighted area sampling • A rough approximation formulated by dividing each pixel into a finer grid of pixels

  9. Unweighted Area Sampling • Primitive cannot affect intensity of pixel if it does no intersect the pixel • Equal areas cause equal intensity, regardless of distance from pixel center to area

  10. Weighted Area Sampling • Unweighted sampling colors two pixels identically when the primitive cuts the same area through the two pixels • Intuitively, pixel cut through the center should be more heavily weighted than one cut along corner

  11. Intensity W(x,y) x Weighted Area Sampling • Weighting function, W(x,y) • specifies the contribution of primitive passing through the point (x, y) from pixel center

  12. Images • An image is a 2D function I(x, y) that specifies intensity for each point (x, y)

  13. Sampling and Image • Our goal is to convert the continuous image to a discrete set of samples • The graphics system’s display hardware will attempt to reconvert the samples into a continuous image: reconstruction

  14. Point Sampling an Image • Simplest sampling is on a grid • Sample dependssolely on valueat grid points

  15. Point Sampling • Multiply sample grid by image intensity to obtain a discrete set of points, or samples. Sampling Geometry

  16. Sampling Errors • Some objects missed entirely, others poorly sampled

  17. Fixing Sampling Errors • Supersampling • Take more than one sample for each pixel and combine them • How many samples is enough? • How do we know no features are lost?

  18. Unweighted Area Sampling • Average supersampled points • All points are weighted equally

  19. Weighted Area Sampling • Points in pixel are weighted differently • Flickering occurs as object movesacross display • Overlapping regions eliminates flicker

  20. How is this done today?Full Screen Antialiasing • Nvidia GeForce2 • OpenGL: scale image 400% and supersample • Direct3D: scale image 400% - 1600% • 3Dfx Multisampling • 2- or 4-frame shift and average • Nvidia GeForce3 • Multisampling but with fancy overlaps • ATI SmoothVision • Programmer selects samping pattern • Tradeoffs…

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