Robotic Camera Extension Takes Gigapixel Photos
schliz writes "Scientists at Carnegie Mellon University have developed a device that lets a standard digital camera take pictures with a resolution of 1-gigapixel (1,000-megapixels). The Gigapan is a robotic arm that takes multiple pictures of the same scene and blends them into a single image. The resulting picture can be expanded to show incredible detail."
How true. Another example of people in computer vision with no ideas who are stealing from people who don't sell themselves well enough. What a sad subject computer vision has become. See Adam Kropps paper with Seth Teller here on spherical mosaics.
So, basically it can do the exact same thing as Photoshop, except with the added expense and complications of a robotic arm. Way to go, Carnegie Mellon.
I think this just proves that higher resolution doesn't result in a higher quality photo.
If you look at the entire photo it doesn't look any better than a regular photo even if it contains much more information.
For years now there has been a push to larger and larger resolution photos with people often mistaking this with "quality."
All a higher resolution really allows you to do is zoom in more after a certain point. Which is awesome from a photo editing point of view, but for most people unimportant.
What you really want to be focusing on is the lens quality, zoom quality (lol Digital Zoom), noise, and other characteristics of the camera (e.g. ISO rating).
So it is great that they spent lot's of time doing this but it isn't all that interesting to average Joes or even serious photographers. We all really want better quality pictures, not bigger ones.
to my understanding, resolution refers to a mapping of the object on to the image - resolution is a ration of 1 cm in object/x cm in image
it has nothing to do with pixels per image, although you can have more of the object , at the same resolution, with more pixels
Well its a good idea to check before they submit for a patent, since there is prior art.
Also, the MIT work is well known to anyone in this area. It's not that hard to google some of the keywords and get the MIT page. The CMU people either knew and ignored it, or they simply didn't do what most of the scientists at their institution usually do, which is read the standard conference papers in computer vision, and browse the web (just a little!!). It's not as if the MIT work was published in some obscure place.
True, you can put together a lot of composite pictures to achieve an arbitrary size and resolution. You can legitimately call the result a gigapixel picture (if it reaches the resolution requirement, of course). But that shouldn't be confused with a gigapixel camera, and in and by itself is not actually that impressive.
For example, if you take the entire photoset of Google Earth, you'd probably get a few peta-pixels worth of data. Ultimately, it all boils down to how much of that data is needed at any given time. You might need a low-detail, large-area image (e.g. view of Earth as a whole), or a high-detail, small-area image of your backyard. In either case, you wouldn't need more than at most a few dozen megapixels at any given time. It's unlikely anyone ever needs more than that size, whether they are studying galaxies or atoms, because the more detail you need, the less physical area you need covered, and vice versa.