Advances promise lower power to capture digital images
Researchers at the University of Rochester in Rochester, NY, have developed two technologies that they said will significantly reduce the amount of power required to capture a digital image.
If adopted by ENG camera manufacturers someday, the new technology could help to extend the use of batteries between recharges.
Mark Bocko, professor of electrical and computer engineering, and Zeljko Ignjatovic, assistant professor of electrical and computer engineering, have designed a prototype chip that can digitize an image right at each pixel. They also are working on another technology to compress an image with fewer computations than the best current compression techniques.
One of the technologies integrates an oversampling analog-to-digital converter at each pixel location in a CMOS sensor. Previous attempts to do this on-pixel conversion have required many transistors, leaving too little area to collect light. The Rochester designs use as few as three transistors per pixel, reserving nearly half of the pixel area for light collection.
Initial tests show that at video rates of 30fps, the designs use 0.88 nanowatts per pixel —50 times less than the industry's previous best. It also delivers a dynamic range of 1:100,000–a hundredfold improvement over existing CMOS sensors.
The team’s other advance is called Focal Plane Image Compression. Bocko and Ignjatovic have figured out a way to arrange photodiodes on an imaging chip so that compressing the resulting image demands as little as 1 percent of the computing power usually needed.
Normal compression techniques include a discrete cosine transform, which checks how much a segment of an image resembles a series of cosine waves. Both the image and the cosine waves are sampled at regular intervals and the transform requires that the image and cosine wave samples be multiplied together and added. Since the cosine wave samples can have a value anywhere between -1 and +1, the computation requires multiplication by non-integers, which demands the bulk of the computing power.
But Ignjatovic and Bocko have laid out the pixels to lie at the peaks of cosine waves resulting in a non-uniformly distributed array, instead of an evenly spaced one. By using this trick, the amount of computation required to compress the image is slashed by nearly five-fold.
For more information, visit www.rochester.edu.
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