Ever taken a digital photograph and then found out you had missed the fine details that made the scene so impressive visually? Many imaging devices produce signals of unsatisfactory resolution (e.g. a photo from a cell-phone camera may have low spatial resolution or a video from a web camera may have both spatial and temporal low resolution). Applying a Photoshop sharpen filter may make the photo appear sharper, but such filters are lossy – they actually reduce the amount of fine detail in the image.

This method applies digital processing to reconstruct more satisfactory high resolution signals. Previous methods for Super-Resolution (SR) require multiple images of the same scene, or else an external database of examples. This method provides the ability to perform SR from a single image (or a single visual source). The algorithm exploits the inherent local data redundancy within visual signals (redundancy both within the same scale, and across different scales). This super-resolution process pulls unseen details from the nooks and crannies of a single digital photograph. Their process can capture true detail which cannot be seen in the original image.

Examples of the methods' capabilities can be found here:

http://www.wisdom.weizmann.ac.il/~vision/SingleImageSR.html