BE-CALF

BE-CALF: Bit-Depth Enhancement by Concatenating All Level Features of DNN

Instructions:

1. install TensorFlow(GPU);
2. run 4-16/test_416.py to recover 16-bit images from 4-bit versions.
   run 8-16/test_816.py to recover 16-bit images from 8-bit versions.
   It will directly compress and reconstruct images from test/.
3. Results output to results_416/ or results_816/.

• The image size in the code needs to be changed.

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If you use this code, please cite the following publication:
J.Liu, W.Sun, Y.Su, P.Jing, X.Yang, "BE-CALF: Bit-Depth Enhancement by Concatenating All Level Features of DNN", to appear in IEEE TRANSACTIONS ON IMAGE PROCESSING

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This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

For a copy of the GNU General Public License, please see http://www.gnu.org/licenses/.

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Here we thanks Christian Ledig et al. who are authors of "Photo-realistic single image super-resolution using a generative adversarial network", published in IEEE Conference of Computer Vision and Pattern Recognition, for referring to their outstanding work.

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