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A Single Pixel Camera
BuzzSkyline writes "Scientists at Rice University have developed a one pixel camera. Instead of recording an image point by point, it records the brightness of the light reflected from an array of movable micromirrors. Each configuration of the mirrors encodes some information about the scene, which the pixel collects as a single number. The camera produces a picture by psuedorandomly switching the mirrors and measuring the result several thousand times. Unlike megapixel cameras that record millions of pieces of data and then compress the information to keep file sizes down, the single pixel camera compresses the data first and records only the compact information. The experimental version is slow and the image quality is rough, but the technique may lead to single-pixel cameras that use detectors that can collect images outside the visible range, multi-pixel cameras that get by with much smaller imaging arrays, or possibly even megapixel cameras that provide gigapixel resolution. The researchers described their research on October 11 at the Optical Society of America's Frontiers in Optics meeting in Rochester, NY."
It would be indeed impractical, and that makes this method quite useless in most applications. The researchers asked themselves "what if that single pixel receptor is good and expensive" while most modern answers are quite opposite to that - it's easier to make plenty of medium quality sensors than one good sensor. Not even counting the micro-mechanics needed. Solid state already gives you several megapixels for a few dollars, and the cost is only going down.
within a certain wavelength range (down to where actual atomic structures break up the smoothness), a perfectly flat material with no resistance has perfect reflection (that's why the silver back on a glass mirror is so reflective, is very flat and conductive
Instead of using micro mirrors, the Los alamos team used an LCD which were more mature at the time. And Instead of using random modulation they used a progression of zenike polynomials and thus achieved much more control over the data compression.
Some drink at the fountain of knowledge. Others just gargle.
Actually a less fancy version of this technique was already used on mars pathfinder where several images were taken of the same objective and then combined to obtain better resolution.
"Superresolution image processing is a computational method for improving image resolution by a factor of n[1/2] by combining n independent images. This technique was used on Pathfinder to obtain better resolved images of Martian surface features."
Taken from the abstract of this article:
A patent for "A single element detector acts as an array"
The technique in use for years for infra-red cameras involves the use of a single (Peltier-cooled) pixel and a scanner, but scanners have numerous problems one of which is that there is always vibration caused by the two frequency components of the line end switching of the horizontal and vertical scans. This technique, by using pseudo-random switching, should eliminate vibration.
So the ultimate long term goal would appear to be the ability to produce 3-D images with focus throughout the entire scene, low light capability and an absence of blur due to vibration. IANAOR (I am not an optical researcher) but it seems a good line of investigation.
Pining for the fjords
Is it really cheaper to manufacture micromirror arrays that CCD or CMOS sensors?
Not likely. And it certainly doesn't sound mechanically robust to have moving parts replace a purely electronic chip. Cameras need to be rugged.
Also, what degree of photon loss do you have from the arrays? No mirror is perfect...
Imperfection in the reflectivity is probably secondary to diffraction, which will be a big problem for these small mirrors - and they would have to shrink even further for reasonable (multi-Mpixel) image resolutions. Diffraction is the biggest limiting factor for contrast in DMD projectors.
There are other problems with this design. First off, it is a time-sequential acquisition. The reconstruction algorithm assumes that all measurements are taken from the exact same scene. God knows what garbage it produces if you have moving objects or camera shake.
I guess their biggest motivation is to do the image sensing directly in compression space. Unfortunately, their compression space is vastly inferior to the compression space of, say JPEG. You see, JPEG is very cleverly designed in that it doesn't actually zero out certain frequencies directly - it just quantizes higher frequencies more agressively than lower ones, and that results in data that compresses better with a lossless compression algorithm (Huffman). By contrast, this compressive camera thing essentially directly zeroes out certain frequencies that have low amplitude. Not a very good idea perceptually.
That's vive la différence. Difference is a girl in French. :)
No real French speaker would make this kind of mistake...
Like a lot of people who do not know any optics, I suspect you think that the light at the scene is somehow concentrated by the lens to form the image. It isn't; the lens doesn't suck in any extra light other than what impinges on it.
A single pixel is effectively approx f/1.
Oh yes, and you are arrogant, rude, and stupid. Perhaps you really do have a job with Microsoft.
Pining for the fjords
No camera system is perfect... but I think you might be selling this one short a little too soon.
The idea behind the average consumer camera is to gather photons from a large area in a reasonably short amount of time. Usually we do this with film or with a CCD or CMOS array. However, film is going out of vogue, and CCDs and CMOS arrays can have dead spots. From a scientific standpoint, arrays are problematic for this very reason... plus, who has time to calibrate several thousand detector elements per camera? Using a single element detector helps mitigate this problem.
In this ScienceDaily article, it is revealed that the system works best with higher frequency information that can appear to be white noise. While it may produce images that are unappealing to the human eye, from a scientific standpoint it might be just the thing needed for a given application. I'd be very careful stating that it "essentially directly zeroes out certain frequencies that have low amplitude"... a more appropriate description of what it is doing is recording less information for fields that contain little or no change. Change is often edges, and edges are approximately generated through the summation of many high-frequency sinusoids.
From an imaging standpoint, this is some intriguing stuff. I would have gone to the presentation, but I had class at the time.