Photo-realistic residual bit-depth enhancement by advanced conditional GAN
- Install TensorFlow(GPU);
- Download BE-ACGAN model from Baidu Drive(4m43) to
./model/ - Run 4-8/test_4_8.py to recover 8-bit images from 4-bit versions.
Run 4-16/test_4_16.py to recover 16-bit images from 4-bit versions.
It will directly compress and reconstruct images from testdata/. - Results output to results_48/ or results_416/.
- The image size in the code needs to be changed.
If you use this code, please cite the following publication:
J.Zhang, Q.Dou, J.Liu, Y.Su, W.Sun, "BE-ACGAN: Photo-realistic residual bit-depth enhancement by advanced conditional GAN", to appear in Displays
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/.
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.