From small to not so pixel-perfect large

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.

Ansprechpartner:
Prof. Dr. Bernhard Schölkopf
Max Planck Institut für Intelligente Systeme
Tübingen
Tel. +49 7071 601 551
bernhard.schoelkopf@tuebingen.mpg.de

Presseveröffentlichung vom 27.10.2017

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