Super-Resolving Compressed Images via Parallel and Series Integration of Artifact Reduction and Resolution Enhancement
Hongming Luo, Fei Zhou, Guangsen Liao, Guoping Qiu.
We collect 76 uncompressed images by ourselves to supplement Kodak24 (http://r0k.us/graphics/kodak/). These images are selected from 1000 images with the size of 3840 * 2160 and cropped as images with the size of 600 * 600. They are from a variety of scenarios including indoors, outdoors, and so on. We prepare these data using MATLAB.
We also build up a dataset containing 50 avatar images from the social media WeChat. Specifically, 5 WeChat users (3 females and 2 males) are selected, and each user is required to provide 10 avatar images from their friend lists after the approval from their friends.
Some results are shown in the following Section, as well as the rest of results can be downloaded in Section. 6.
Download dataset links: VISTA_UCD76_dataset.zip and VISTA_WeChat50_dataset.zip
Thumbnail of UCD76 dataset images.
Thumbnail of WeChat avatar dataset images.
Involved methods: SA_DCT , TNRD , DnCNN , DCSC . Among these compared methods, the inputs of SA_DCT and TNRD are limited to JPEG images. Thus, they are not able to restore WebP images. The best performance is bold and the second one is underlined in the following table.
All of our results are available at：
Baidu Drive link :(https://pan.baidu.com/s/1eF41V3jnQnR_1CwuD1PYkA) password (1xuj)
Google Drive (https://drive.google.com/drive/folders/13oJ1lb-GuAM1OEg6QiXV_gHJ3_y9vlzS)
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