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."

Comments

Not so novel

[Anonymous Coward]

Seth Teller at MIT EE was doing this 8 years ago. Check out his Cityproject.

Re:Not so novel

[2.7182]

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.

Re:Not so novel

[Clover_Kicker]

You know what they say, a month in the lab can often save an afternoon in the library.

ALE

[pipatron]

Also check out Anti-Lameness Engine, http://auricle.dyndns.org/ALE/ which does exactly the same thing, but you have to provide your own arm.

But can't you infinitely zoom into a normal photo?

[CRCulver]

After all, they do it all the time on CSI.

1000 megapixel?

[duguk]

From TFS:

take pictures with a resolution of 1-gigapixel (1,000-megapixels)

Where's the other 24 megapixels? ;)

caveat: yes, i know. don't start. it was a joke. don't link to wikipedia to explain, besides; xkcd explained it better.

Re:Any superresolution software for average Joe?

[Sitnalta]

Yep. Open Adobe Photoshop and go to File -> Automate -> Photomerge. Then simply point it to the folder containing your photo array.

Higher Resolution != Higher Quality

[Manip]

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.

Re:Higher Resolution != Higher Quality

[RichardKaufmann]

You're confusing three different aspects of quality:

1. Resolution (the number of pixels in am image, here increased by stitching overlapping images)
2. Dynamic range, color fidelity, noise (the quality of a particular pixel). This can be somewhat ameliorated by HDR photography or just averaging identical shots (all with no moving subjects and a sturdy tripod). Google Photomatix for details.
3. Whether the shot is interesting, well composed, in focus, without motion blur, etc. Panorama photography is most interesting for its artistic potential; more pixels is just a delightful side effect.

#1 and #2 can be addressed by money and a willingness to prostrate yourself to the camera gods. #3 requires talent!

And to put a final nail in the megapixel coffin: check out http://www.luminous-landscape.com/essays/Equivalent-Lenses.shtml (particularly Nathan Nyhrvold's comments) for a discussion of how sensor size and f-stop place an upper bound on resolution irrespective of sensor density. Physics can be a pain sometimes!

Big Deal!

[Evildonald]

I've been doing this for years with a film camera and then sticky-taping all the photos together. Then when i want to "zoom in" I just move my head closer to the picture.

Another entry into the market is always welcome

[AsmordeanX]

That's not really all that new. Motorized panorama heads have been around for a long time. People have even built them from Lego Technics.

As an avid pano/gigapixel photographer myself I'm interested in any new entry into the excessively priced head market. I'm using a Kadian Quickpan Pro that cost me $400 a few years ago. An automated system would be very nice but the cost is usually horrific. I've even had a head custom built at one point.

As for the use, I like to take big pictures. I have a 6ft x 3ft print hanging on my wall. The print is 400dpi taken from a 43000x22000 (just shy of 1GP). People see the picture and say it looks nice then walk a little closer, and closer, and closer. Pretty soon they are standing 4" away and excitedly reading the serial number on the front of a train car that is only 2" across on the print.

We Did It in 1990

[Doc Ruby]

I worked for a SF area startup in 1990 that produced and sold cameras for "digital prepress" (later called "desktop publishing", and now just "publishing" ;) that had the highest resolution around, to compete with drum scanners that were then the expensive industry standard equipment.

We took a 512x512 Hitachi video sensor with a 2x2 C-M/Y-K mask repeated over it, for initial 1Kx1Kx40bit images that we derived from DSP on the intensity of the color-masked pixels. Then we physically stepped the sensor through 8x8 subpixel shifts, subsampling each pixel 64x. We ran the resulting 320MB raw composite files through a bank of multiple 25MFLOPS DSPs (interconnected and logic-accelerated by a fat FPGA) to produce 4Kx4Kx36bit 72MB files. In 1990 that was an awesome achievement.

We poured dramatic engineering work into that platform, which replaced a $150K drum scanner with a $30K PC (on DOS or Win3.0, or plus optional $5K Mac with its GUI including Photoshop 1.0). We had to deal with DSP for micropositioning the video sensor quickly (using feedback data from a laser/interferometer), with new color spaces (I was part of the JPEG org that produced the image format), with custom interconnects at blazing bandwidth, with parallel multiprocessing at then-supercomputer speeds written in C on DOS, and even with the physics of the light variably distorted by turbulence in the air between the camera and scanned slides, heated by the hot lights necessary for exposures fast enough to allow 64 frames and rescan before the sensor wiggled.

All for a 16Mpxl camera that's now beaten by big sensors on handheld consumer devices for under $2K (in 2008, not 1990, dollars). But I can proudly say that we beat them by almost 20 years.