ABSTRACT

This chapter focuses on mapping hyperspectral imaging algorithms to graphics processing units (GPU). The performance and parallel processing capabilities of these units, coupled with their compact size and relative low cost, make them appealing for onboard data processing. We begin by giving a short review of GPU architectures. We then outline a methodology for mapping image processing algorithms to these architectures, and illustrate the key code transformation and algorithm tradeoffs involved in this process. To make this methodology precise, we conclude with an example in which we map a hyperspectral endmember extraction algorithm to a modern GPU.