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Single image upscaling 1. large2. realistic3. faithful4. fast 1. large2. realistic3. faithful4. fast.

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Presentation on theme: "Single image upscaling 1. large2. realistic3. faithful4. fast 1. large2. realistic3. faithful4. fast."— Presentation transcript:

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3 Single image upscaling 1. large2. realistic3. faithful4. fast 1. large2. realistic3. faithful4. fast

4 Previous work parametric image model example based Freeman et al generic looking edges Sun et al Shan et al 2008 Fattal 2007 Glasner et al noisy result noisy result

5 New approach: locale example based corner step edge line step edge non smooth shading local self similaritysmall upscaling ratios 1/2 4/5 new non-dyadic filter bank locality too few examples Increase exemplar quality and size maintain search locality Increase exemplar quality and size maintain search locality

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7 Local self-examples upscaling low pass original image high pass interpolated image frequency content frequency content

8 low pass high pass interpolated image For each patch: Search a local area for best example Take corresponding patch Add to interpolated image frequency content frequency content Local self-examples upscaling

9 low pass high pass interpolated image Repeat for all patches, to fill the high frequencies frequency content frequency content

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11 Local self similarity

12 Patches in original image can matched locally with ones in downscaled version

13 Local examples are enough full image image database query db image local best matches

14 Visual assessment – external, exact NN, local Large external example database Large external example database Searching the entire image Searching the entire image Searching local regions in image Searching local regions in image

15 Comparison of example search methods

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17 Need for non-dyadic scalings large ratios mixed ratios small ratios

18 Dyadic filters 1:2 full frequency content higher half lower half dyadic filter bank

19 Non-dyadic filter bank 1:2 4:5 small scaling ratios better examples full frequency content higher part lower part non-dyadic filter bank

20 Non-dyadic filters: downscaling 1. convolve with 2 filters 2. subsample each by 3 dyadic case: example for the 2:3 ratio: 1. convolve with one filter 2. subsample by 2

21 Non-dyadic filters: upscaling 1. zero upsample by 2 2. convolve with 2 filters 3. sum dyadic case: example for the 2:3 ratio: 1. zero upsample by 1 2. convolve with 1 filter

22 Use of the filters in upscaling Upscaling using inverse scaling filters Smoothing by downscaling and upscaling

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24 When interpolating, smooth areas come from input Uniformly spaced grids should remain uniform 1. Uniform stretch brightness grid coordinates

25 2. Consistency upsample downsample Previous methods achieve consistency by solving large linear systems to achieve this property

26 3. PSF modeling 3. PSF modeling Large image - small camera point spread function Small image - large camera point spread function Difference between point spread functions Difference between point spread functions

27 4. Low frequency span 4. Low frequency span frequency When upsampling don’t add new frequencies Upsampling filter should be low-pass original interpolated

28 5. Singularities preservation 5. Singularities preservation blurred Image interpolated image similar amount of blur similar amount of blur

29 Real time video upsampling on GPU main GPU memory GPU cores NTSC to full 24 fps Search and filter-banks are both local operations Search and filter-banks are both local operations

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31 Bicubic x3 (zoomed in) Ours X3 (zoomed in)

32 Bicubic x3 Ours X3

33 Genuine Fractals™ x4 Ours X4

34 Glasner et al x4 Ours X4

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37 Paper & additional results can be found at:


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