SI
SI
discoversearch

We've detected that you're using an ad content blocking browser plug-in or feature. Ads provide a critical source of revenue to the continued operation of Silicon Investor.  We ask that you disable ad blocking while on Silicon Investor in the best interests of our community.  If you are not using an ad blocker but are still receiving this message, make sure your browser's tracking protection is set to the 'standard' level.
Technology Stocks : C-Cube -- Ignore unavailable to you. Want to Upgrade?


To: John Rieman who wrote (34239)7/9/1998 5:35:00 PM
From: Don Dorsey  Respond to of 50808
 
Product Profile
Researchers at NASA's Ames Research Center have significantly advanced the state-of-the-art of digital image compression. From cable TV to high speed copiers, a wide array of today's electronic imaging products utilize the power of digital imaging. NASA Ames has developed DCTune, a computer technology that significantly improves efficiencies in storage
and transmission of documents, pictures and videos. This technology is compatible with industry compression standards known as JPEG and MPEG. DCTune can be used as add-on modules of software to existing imaging workstation software or imaging devices, or as add-on functions to existing microchip designs.

The Technology

The DCTune technology represents a fundamental improvement on existing optimization techniques known as Quantization. Quantization selectively increases or decreases the amount of information used to render a picture. This selective allocation is based on the anticipated sensitivity of the human eye to the target portion of the image. If the eye is sensitive to the targeted
portion then more picture information will be used. Previous techniques took an averaging approach to determine the eye's sensitivity toward brightness and contrast. This leads to over allocation of information in portions of the image where the eye is not as sensitive as represented. However in the DCTune technology the sensitivity behavior of the human eye is accurately modeled and it is thus able to precisely determine the amount of information needed for each image. The net result is consistently better image quality and higher compression efficiency.

usc.edu