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  • 1 Markov network True Original 50x58 The Markov network algorithm hallucinates those vertical rectangles that it was trained on. Training images
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1 Markov network True Original 50x58 The Markov network algorithm hallucinates those vertical rectangles that it was trained on. Training images

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Page 1: 1 Markov network True Original 50x58 The Markov network algorithm hallucinates those vertical rectangles that it was trained on. Training images

1

Markovnetwork

True

Original50x58

The Markov network algorithm hallucinates those vertical rectangles that

it was trained on.

Training images

Page 2: 1 Markov network True Original 50x58 The Markov network algorithm hallucinates those vertical rectangles that it was trained on. Training images

2

True

Original50x58

Training images

Now train on a generic collection of images.

Page 3: 1 Markov network True Original 50x58 The Markov network algorithm hallucinates those vertical rectangles that it was trained on. Training images

3

Markovnetwork

True

Original50x58

The algorithm makes a reasonable guess at the high resolution image, based on its

training images.

Training images

Page 4: 1 Markov network True Original 50x58 The Markov network algorithm hallucinates those vertical rectangles that it was trained on. Training images

4

Generic training images

Next, train on a generic set of training images. Using the same camera

as for the test image, but a random collection of

photographs.

Page 5: 1 Markov network True Original 50x58 The Markov network algorithm hallucinates those vertical rectangles that it was trained on. Training images

5

Cubic Spline

Original70x70

Markovnet, training:generic

True280x280

Page 6: 1 Markov network True Original 50x58 The Markov network algorithm hallucinates those vertical rectangles that it was trained on. Training images

6

Kodak Imaging Science Technology Lab test.

3 test images, 640x480, to bezoomed up by 4 in each dimension.

8 judges, making 2-alternative, forced-choice comparisons.


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