Scientists at the Max Planck Institute for Intelligent Systems in Tübingen utilize the Artificial Intelligence of a software to create a high definition version of a low resolution image. While the pixel-perfectness is being sacrificed, the reward is a better result.
Paper presented at ICCV 2017, Venice:
Everyone knows this problem: a friend sends a low-resolution image of last weekend´s hike to your smartphone, but when you save the picture of the beautiful bird and later add it to a digital photo album, the image shows checkerboard artifacts.
The resolution is just too low. In times of need software is utilized that promises to upsample small sized images, but with poor results: Those holiday pictures look blurry and lack high definition.
Technology to create a large size from a low-resolution image is known as the single image super-resolution or SISR technology. SISR has been studied for decades, but with limited results. The software adds extra pixels and fills them with the average “look” of all the surrounding pixels.
The result is blurriness. Researchers at the Max Planck Institute of Intelligent Systems propose a new approach to give images a realistic texture when magnified from small to large – through the help of Machine Learning. Artificial Intelligence is at play, where the algorithm for upsampling the image learns from experience in sharpening its look.
The learning process is much like that of a human: practice makes the master. “The algorithm is given the task of upsampling millions of low resolution images to a high resolution version and is then shown the original, the “this-is-how-it-should-be”-image.
Notice the difference? OK, then learn from your mistake”, explains Mehdi M.S. Sajjadi, who together with Dr. Michael Hirsch and Prof. Dr. Bernhard Schölkopf, Director of the Empirical Inference Department at the Max Planck Institute for Intelligent Systems in Tübingen, developed the EnhanceNet-PAT technology. Once EnhanceNet-PAT is trained, it no longer needs original photos.
When EnhanceNet-PAT is put to work, according to the researchers, the technology is more efficient than any other SISR technology currently on the market. The difference lies in the pretense of wanting to be pixel-perfect. In contrast to existing algorithms, EnhanceNet-PAT gives up on pixel-perfect reconstruction, but rather aims for faithful texture synthesis.
By being capable of detecting and generating patterns in a low resolution image and of applying these patterns in the upsampling process, EnhanceNet-PAT thinks how the bird´s feathers should look like and adds extra pixels to the low-resolution image accordingly. You could say the technology created its own reality. For most viewers, the result is very much like the original photo. The picture of the bird is good to adorn the photo album.
Claudia Däfler | Max-Planck-Institut für Intelligente Systeme
Researchers greenlight gas detection at room temperature
27.10.2017 | Moscow Institute of Physics and Technology
Secure payment without leaving a trace
26.10.2017 | Karlsruher Institut für Technologie (KIT)
Cancer cells can reactivate a cellular process that is an essential part of embryonic development. This allows them to leave the primary tumor, penetrate the surrounding tissue and form metastases in peripheral organs. In the journal Nature Communications, researchers from the University of Basel’s Department of Biomedicine provide an insight into the molecular networks that regulate this process.
During an embryo’s development, epithelial cells can break away from the cell cluster, modify their cell type-specific properties, and migrate into other...
For the second time, Dr. Samuel Sánchez from the Max Planck Institute for Intelligent Systems in Stuttgart receives the Guinness World Record for the smallest nanotube travelling through fluid like a jet engine.
Dr. Samuel Sánchez is thrilled, just like last time he received a Guinness World Record for the smallest jet engine ever created. Sánchez is a Research Group...
Salmonellae are dangerous pathogens that enter the body via contaminated food and can cause severe infections. But these bacteria are also known to target...
University of Maryland researchers contribute to historic detection of gravitational waves and light created by event
On August 17, 2017, at 12:41:04 UTC, scientists made the first direct observation of a merger between two neutron stars--the dense, collapsed cores that remain...
Seven new papers describe the first-ever detection of light from a gravitational wave source. The event, caused by two neutron stars colliding and merging together, was dubbed GW170817 because it sent ripples through space-time that reached Earth on 2017 August 17. Around the world, hundreds of excited astronomers mobilized quickly and were able to observe the event using numerous telescopes, providing a wealth of new data.
Previous detections of gravitational waves have all involved the merger of two black holes, a feat that won the 2017 Nobel Prize in Physics earlier this month....
23.10.2017 | Event News
17.10.2017 | Event News
10.10.2017 | Event News
27.10.2017 | Life Sciences
27.10.2017 | Physics and Astronomy
27.10.2017 | Physics and Astronomy