What is super-resolution?
Super-Resolution is a method of getting a high resolution image from a low resolution one. There are various techniques for achieving Super-Resolution.
Techniques to achieve super-resolution
Traditional techniques
Before the appearance of modern techniques, images were enlarged by using interpolation methods like Nearest Neighbor, Bilinear or Bicubic, each one outputting better results than the previous one, in that order.
Modern techniques (based on Artificial Intelligence)
Modern techniques are represented by Machine Learning algorithms. Using neural networks to improve super resolution results has been shown to create images with more details and vivid colors than before, and the improvements are only getting better as more research goes into the topic.
How does ImgUpscale work?
ImgUpscale takes the second approach to achieve Super-Resolution and uses Neural Networks for enhanching the resolution of the images.
Let us know if you have used ImgUpscale by writing us a message on the Contact page
How can Super Resolution help you?
Graphic Design & Art
You don't need expensive equipment to create beautiful pieces of art. By enhancing the resolution of your precious photos you can keep the costs down and concentrate on what matters: delivering high-quality prints.
Satellite Imagery
One of the use-cases where super-resolution can help is parcel boundaries. You can have the same results, but at a lower cost by choosing to enhance a low-resolution satellite imagery instead of paying a lot more for high-resolution providers.
Medical Imagery
High resolution imagery is quite difficult to capture, especially when we talk about MRI. It takes a lot of time and it puts lots of pressure on the patient. With the help of Super-Resolution things might change for both the patient and the doctor. However, because it is a very sensitive domain, the algorithms that perform super-resolution in medicine need to be approved by certain authorities before using them on a large scale.
Image compression
Enhancing the resolution at a certain moment can reduce server costs. sending images at low-resolution and upscale afterwards
