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CS248 Midterm Review. CS248 Midterm Mon, November 3, 7-9 pm, Gates B01 Mostly “short answer” questions – Keep your answers short and sweet! Covers lectures.

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Presentation on theme: "CS248 Midterm Review. CS248 Midterm Mon, November 3, 7-9 pm, Gates B01 Mostly “short answer” questions – Keep your answers short and sweet! Covers lectures."— Presentation transcript:

1 CS248 Midterm Review

2 CS248 Midterm Mon, November 3, 7-9 pm, Gates B01 Mostly “short answer” questions – Keep your answers short and sweet! Covers lectures up to Tuesday, Oct 28 – plus taxonomy from start of last lecture Review session slides available from class website Exam is closed book, closed notes

3 Raster Displays, Resolution, Perception Measures of spatial resolution – physical vs. addressable resolution CRTs – 3 phosphors for “red”, “green”, and “blue” – Triads and shadow mask

4 Human spatial frequency sensitivity – Sensitivity highest in fovea – Frequency sensitivity – Phase sensitivity (Vernier acuity) – Temporal sensitivity Flicker (50-70Hz) Perceived motion –12 Hz = cartoons, 24 Hz = film, 60 Hz = video

5 Raster Displays, Resolution, Perception Human intensity sensitivity – Response to intensity is nonlinear – Gamma in cameras, CRTs – Gamma correction Dithering – Trade off spatial resolution for intensity res.

6 Raster Displays, Resolution, Perception Sample (easy) questions: 1. A scene is photographed with a TV camera with gamma=0.5 and displayed on a CRT with gamma=2.4. If we want system gamma to be 1.0, we should do gamma correction with what exponent? 2. You are doing clustered-dot dithering on an image for output on a 300 dpi laser printer. If you need at least 75 dpi “effective” resolution, how many shades of gray can you output?

7 Color Perception of color – Humans are trichromat Three cones sensitive to “red”, “green”, and “blue” – Overlapping response curves Know their general shapes! Color matching – Color matching experiment

8 Color spaces Linear colorspaces – , ,  space (perceptual stimulus) – R, G, B space – X, Y, Z space Non-linear colorspaces – HSV Spectral locus Gamut of reproducible colors

9 Color Sample questions: 1. Can your printer necessarily reproduce all colors that your monitor can reproduce if they both use RGB primaries? 2. You are wearing glasses that block all light from the lower third of the visible spectrum, what color does the world look tinted?

10 Color Sample questions: 3. Circle those colors that are not reproducible with a single monochromatic light 1.Red 2.Yellow 3.Blue 4.Magenta 5.White 6.Green

11 Color Sample questions: 4. If you had a special CRT that could produce pure spectral colors, how many spectral colors would you need to represent a normal RGB color gamut? How about the spectral locus?

12 Digital Compositing The compositing approximation – Conditions for validity Compositing algebra – Know the operations and their effect on an image

13 Digital Compositing Sample question: You are doing the special effects for a movie, and need to composite a computer generated object over a live background. Why should you use an 8-bit alpha matte rather than a binary (1-bit) matte, even if the computer-generated object is fully opaque?

14 Rasterization Rasterization of lines – DDA, incremental algorithm Rasterization of polygons – Only pixels in the polygon Supersampling – Patterns: understand its effect on the image

15 Rasterization Sample question: – If you rasterized this line using DDA, which pixels would get turned on?

16 Transformations Homogeneous coordinates – why? Matrices rotation, translation, scale, shear in 2D, 3D – Know the form of each kind – Geometric properties preserved/changed by each kind Composing transformations – multiply matrices in reverse order

17 Transformations Sample questions Compute the 2D transform that translates an object centered at (-3,4) to the origin, then rotates it by +45 o, then translates it to (10,5). What sequence of transforms would cause the triangle to change as shown below ?

18 Sampling and Antialiasing The sampling and reconstruction pipeline: – Prefiltering – Sampling – Resampling – Reconstruction Aliasing in the frequency domain Filtering and convolution – Duality: F(x)*G(x) F(w)G(w)

19 Sampling and Antialiasing Prefiltering vs. postfiltering Desirable filters for antialiasing – Box, pyramid, gaussian, sinc Methods of antialiasing – Supersampling: regular vs. stochastic – Analytical antialiasing

20 Sampling and Antialiasing Sample questions: 1. What is the result of convolving a 1-D box filter with itself? 2. Which of the following would affect your choice of a reconstruction filter? Pixel shape choice of prefilter actual size of display

21 Sampling and Antialiasing Sample questions: 3. Image: filter: 0 0 0 0 10 20 30 40 0 0 20 0 0 50 0 0 30 0 0 60 0 0 40 60 70 80 0 0 0 0 -1 0 1 -2 0 2 -1 0 1

22 GOOD LUCK AND HAPPY HALLOWEEN!


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