Onboard Image Processing System for Hyperspectral Sensor

Abstract

Onboard image processing systems for a hyperspectral sensor have been developed in order to maximize image data transmission efficiency for large volume and high speed data downlink capacity. Since more than 100 channels are required for hyperspectral sensors on Earth observation satellites, fast and small-footprint lossless image compression capability is essential for reducing the size and weight of a sensor system. A fast lossless image compression algorithm has been developed, and is implemented in the onboard correction circuitry of sensitivity and linearity of Complementary Metal Oxide Semiconductor (CMOS) sensors in order to maximize the compression ratio. The employed image compression method is based on Fast, Efficient, Lossless Image compression System (FELICS), which is a hierarchical predictive coding method with resolution scaling. To improve FELICS’s performance of image decorrelation and entropy coding, we apply a two-dimensional interpolation prediction and adaptive Golomb-Rice coding. It supports progressive decompression using resolution scaling while still maintaining superior performance measured as speed and complexity. Coding efficiency and compression speed enlarge the effective capacity of signal transmission channels, which lead to reducing onboard hardware by multiplexing sensor signals into a reduced number of compression circuits. The circuitry is embedded into the data formatter of the sensor system without adding size, weight, power consumption, and fabrication cost.

A Runtime-Scalable and Hardware-Accelerated Approach to On-Board Linear Unmixing of Hyperspectral Images

“…Hence, no experimental data or performance metrics under space constraints can be found in those works. However, it is also possible to find solutions throughout the literature using GPUs or FPGAs showing potential real-time results [8,9,[29][30][31].…”

FPGA-Based On-Board Geometric Calibration for Linear CCD Array Sensors

“…Williams et al [ 44 ] also investigated an FPGA-based implementation of real-time cloud detection of spaceborne image. Hihara et al [ 45 ] analyzed an on-board image processing system for hyperspectral imagery. All of the efforts mentioned above have shown a promise for FPGA-based implementation of geometric calibration, which is presented in this paper.…”

Mission Planning and System Design for HISA: A Hyperspectral Imaging Satellite for Australia

“…For comparison, HyspIRI produces 1 Terabit of data per orbit 20) and HISUI (onboard ALOS-3) produces 11.52 Terabits daily. 21) To counter this issue, lossless compression is able to reduce the data size while retaining image quality and thus an FPGA implementation of the Fast Lossless compression algorithm 22) is utilised onboard HISA. It has been shown to produce the best compression ratio (3.1:1) and low bits/sample when compared to other compression algorithms.…”