Speakers
Description
This paper introduces the analyses performed while developing a hyperspectral compression technique based on a novel solution able to satisfy the needs, and thus to candidate for, the next generation hyperspectral missions (e.g. the forthcoming Sentinel-10).
The proposed solution leverages the achievements obtained by the OP3C (On-board Processing for Compression and Clouds Classification) technique, evolving it both on the technological and the algorithmic points of view. OP3C is now able to exploit the acquired data’s information content (e.g. their classification) in order to improve compression efficiency. The improved algorithm aims at exploiting a-priori known information in order to help and improve the on-board real time processing tasks. The information to be used on-board are estimations supporting classification and un-mixing (i.e. abundance fraction estimation for each image pixel), based on hyperspectral data background knowledge. In fact, this kind of information can be used directly as results or can support the image compression task. The availability of their preliminary estimations/ approximations on-board makes the innovative knowledge-based compression techniques possible. The knowledge-based compression can also be utilized for an improved understanding of the image’s content, making possible a consequent real time adaptation of the acquisition plan or even transmitting only relevant semantic information to the ground. And this in turn, actually makes possible to expand mission objectives (like real-time event detection, object detection etc.), without any compromise in quality and quantity of the acquired images.
Furthermore, the image content evaluation opens up to a number of possible decisions, such as whether the information content of acquired images justifies their memory and download bandwidth consume or, on the contrary, the cloud cover overcomes the usability threshold, in order to evaluate a sort of priority in access to limited resources.
The outcome of the analyses is to complement the design and development of spaceOP3C as the next generation on-board data processing integrated solution, composed of:
• a complete on-board SW solution for multispectral/hyperspectral satellites, implementing the evolved OP3C payload data compression techniques;
o enhance the features detection functionalities (from cloud cover detection to image classification);
o improve of the baseline algorithm by means of “knowledge based” compression techniques.
• A complete HW/SW partitioning scheme, aimed at the development of a custom configured FPGA module intended to the most demanding processing steps;
| Paper submission | Yes |
|---|
