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CS448f: Image Processing For Photography and Vision Tone Mapping.

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Presentation on theme: "CS448f: Image Processing For Photography and Vision Tone Mapping."— Presentation transcript:

1 CS448f: Image Processing For Photography and Vision Tone Mapping

2 So far

3

4 Tone Mapping Some Images have too much dynamic range to display on a slide: (belgium.hdr)

5 Recall Sharpening Input = Coarse + Fine

6 Tone Mapping Input = Coarse + Fine

7 Tone Mapping Output = Coarse + Fine

8 Tone Mapping Output = Coarse + Fine Tons of strong detail in the bright regions, not enough in the dark regions

9 Tone Mapping Input = Coarse x Fine

10 Tone Mapping Log(Input) = Log(Coarse) + Log(Fine)

11 Tone Mapping Log(Output) = Log(Coarse) + Log(Fine)

12 How should we make the coarse layer?

13 Input

14 Coarse

15 Fine

16 Input

17 Exp(Log(Coarse)*0.7 + Log(Detail))

18 Exp(Log(Coarse)*0.5 + Log(Detail))

19 Exp(Log(Coarse)*0.3 + Log(Detail))

20 Conclusion: You can use a bilateral for tonemapping It’s highly parameter-sensitive Results aren’t great What’s better? – Not much.


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