The penetration of hyperspectral sensing from either airborne or spaceborne platforms into both commercial and defense applications, has given rise to the need for efficient data transmission and storage. This efficiency can be provided by data compression technology that exhibits sufficient compression ratio at no or minimal loss of information and can perform the task in real or near real time. This Phase II SBIR is aimed at optimizing a practical hyperspectral imagery compression process based on adaptive wavelet technologies, and demonstrating its real-time performance on a prototype processor. The developed algorithm will make maximum utility of the unique attributes of hyperspectral imagery in order to achieve high compression ratios. In additon, the proposed compression technology will be capable of both lossless performance, as well as controlled information loss to achieve hgher compression ratios. The prototype hardware will be flexible, programmable and will maximize the use of state-of-the-art COTS components. It is expected that a single board will be capable of performing real-time compression. It will be demonstrated using prerecorded data, and will be delivered to the governemnt for integration into on-going programs such as the ASRP program.
Keywords: Hyperspectral Entropy Coding Adaptive Wavelets Spectral Correlation Wavelet Decompostion
