Autosophy Databases for High-Resolution Images

Parallel network still image compression

Application Proposal: 1998

Abstract: Digital map data, covering wide areas with fine resolution, requires enormous memory facilities, which become very unwieldy to index, maintain, access and distribute. Current image compression methods cannot greatly reduce storage and transmission burdens without compromising data integrity. Furthermore, image compression tends to exacerbate, rather than alleviate, the indexing, processing and search access issues that arise in proportion to the size of the database. Such are all consequences of conventional Shannon-based storage techniques, in which data is considered to have no “meaning.” A new Autosophy information theory, in contrast, stores data entirely according to its content, for both optimized compression and self-indexing. Data storage is hyperspace saturating. The more images already stored in the database, the less additional memory space required to store additional images. The result could be orders-of-magnitude, lossless data compression for text, images, and live video. “Autosopher” are multimedia databases, which organize and index their own internal data storage. A working prototype for text databases has already been developed. This research would add image storage to create a multimedia database. Using a new Content Addressable Read Only Memory, data search access speed would be about one microsecond-per-pixel regardless of database size.

Applications: Autosopher databases, with lossless image and video compression, could be implemented as plug-in modules to optimize multimedia storage and transmission in Personal Computers. The new CAROM could result in compact Terabit-sized memory modules, for use in robotics applications and very large multimedia databases. Overall, this technology could evolve into a next generation of self-learning, brain-like Autosopher with Artificial Intelligence.

Keywords: Autosophy, Lossless data compression Self-learning databases.

Available downloadable documents:

Proposal document – MS Word doc

Related Publication 2004 – Webpage htm