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ENDS 375

ENDS 375. Foundations of Visualization 9/20/05 Notes. Image Statistics. Useful input into computational algorithms measures of image quality basis for automated decisions about images. Image Statistics. Arithmetic Mean mean = sum(P xy )/(x*y) Variance

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ENDS 375

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  1. ENDS 375 Foundations of Visualization 9/20/05 Notes Visualization Laboratory, Texas A&M University

  2. Image Statistics • Useful input into computational algorithms • measures of image quality • basis for automated decisions about images Visualization Laboratory, Texas A&M University

  3. Image Statistics • Arithmetic Mean mean = sum(Pxy)/(x*y) • Variance variance = (sum(Pxy*Pxy)/(x*y)-mean*mean) Visualization Laboratory, Texas A&M University

  4. Image Statistics • Standard Deviation stdev = square root (variance) • Histogram • two axis plot of pixel values vs number of pixels • basis for deciding - contrast range, overall brightness, thresholding, ... Visualization Laboratory, Texas A&M University

  5. Visualization Laboratory, Texas A&M University

  6. Point Operations on Images • Numeric Transformation • (often not reversible) • Transfer Functions • Often implemented using look-up tables Visualization Laboratory, Texas A&M University

  7. Specific Operations Unity Invert Visualization Laboratory, Texas A&M University

  8. Specific Operations Contrast Adjustment Higher Lower Visualization Laboratory, Texas A&M University

  9. Specific Operations Threshold Gamma Visualization Laboratory, Texas A&M University

  10. Color Modification Less Red More Yellow Visualization Laboratory, Texas A&M University

  11. Arithmetic Operations Two or more images Cxy = Axy< operation > Bxy • Addition • Subtraction • Averaging, etc ... Visualization Laboratory, Texas A&M University

  12. Logical Operations and, or nand, nor xor, xnor Visualization Laboratory, Texas A&M University

  13. Image Averaging Add corresponding pixels from multiple images then divide by the number of images Visualization Laboratory, Texas A&M University

  14. Alpha Blending Cxy = Axy*Mxy + Bxy*(max -Mxy ) “Blends” two images Need a “matte” image Basis for image compositing Visualization Laboratory, Texas A&M University

  15. Compositing Visualization Laboratory, Texas A&M University

  16. Readings • Course notes section 1-7 • Course notes section 1-8 Visualization Laboratory, Texas A&M University

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