These pictures show how Adobe's Deblurring technology can help put an end to blurry Bigfoot photos forever

Image description: this is perhaps the most famous blurry photo in American history. It was taken by Robert Capa on June 6, 1944. It captured an American soldier landing on Omaha Beach, D-Day, Normandy, France. What you see here is a scanned version (there are multiple versions on the Internet). This photo is interesting to us because it has extremely bad quality. Look at the noise and artifacts added by the scanner. It's an extreme test to our algorithm. 

Still think Adobe’s Image Deblurring technology is fake? Like we said before, this new Photoshop tech will end blurry Bigfoot photos forever! Currently, the deblurring tool only kills camera shake—they can't yet deal with motion blur or defocus blur. Also, their research on deblurring is ongoing so it's very possible that new techniques will allow for even better deblurring.

Check out this before-and-after comparison showing what the feature does to one of the most famous camera-shake photos in history: Robert Capa’s D-Day photograph of an American soldier landing on Omaha Beach.

According to Chief Scientist Jue Wang (the guy who did the demo at Adobe Max):

To me the system does a reasonable job. It recovers some details that you won’t be able to see easily in the original. Of course the noise gets boosted somehow, we applied a small amount of noise removal on the output, but maybe a decent denoising algorithm can help here. The most interesting thing is the estimated blur kernel, or in other words, how Robert Capa moved his camera when he shot this one. The kernel shown above not only depicts the camera trajectory, but also shows how long the camera stays at each spatial location (white means longer, black means shorter). It seems Robert kept the camera steady for a while, then suddenly moved to the left before the shutter closed completely. Of course all these happened in the fraction of time when his shutter was open.

How the deblurring tool works is that Photoshop measures the "blur kernel" which tracks how much the camera moved while taking the picture. In this picture's case, the blur kernel shows the camera moving 55 pixels long:

Blur kernel

Hwanho Sunrise Park in Pohang, Korea

Here are some more examples of the deblurring technology from www.juew.org:

Microsoft Sculpture

"The interesting thing for this example is the person in the photo, you can see an enlarged zoom-in version above. The person has some ghosting artifacts. Why? Because the person is moving fast so she has both motion blur and camera shake blur on her. Since the camera shake is relatively small, the motion blur dominants those pixels, and we are applying wrong blur kernel to those pixels. This is the limitation of the algorithm, you will have to manually remove the artifacts on the person somehow. Future research direction here!"

"To estimate the blur kernel, the algorithm will automatically find some edges that it thinks are "good" or "reliable", based on some criteria. In this case, even there are some lines in the background, the algorithm does not think it can trust those lines, and eventually decide that the image is not blurry. That's why the output kernel is so close to a dot. And, applying this kernel to the image won't change the content much. However, if you are interested in pixel-by-pixel difference, download the full-res images first :)

We agree that the algorithm does not always work well, and this is the case it fails right now. As we improve the algorithm, we hope we can get better result later on. In the meanwhile if you have an algorithm that works better on this example and you'd like to share it with us, we'd like to learn from you."

[via: www.juew.org]