<title>Interaction of onboard transform-based lossy compression algorithms with EO/IR focal plane nonuniformity correction techniques</title>

Abstract

This paper describes the effect of using lossy transform-based compression on infrared framing sensor data with and without sensor anomaly pre-processing. Significant image degradation persists when ground-based non-uniformity correction processing is implemented after the sensor imagery has been compressed and reconstructed. Various techniques for non-uniformity correction, from low to high processing complexity (i.e., standard two-point gain/offset correction, two-point with bad-pixel replacement, adaptive temporal high pass filtering, adaptive neural net non-uniformity correction, etc.), are applied before and after lossy compression at varying compression ratios. Results using both DCT and Wavelet transform-based compression techniques indicate that on-board real-time compression algorithms and nonuniformity correction must be jointly optimized and that direct application of lossy compression without preprocessing for sensor anomalies reduces not only the compression efficiency and image fidelity, but also the performance of subsequent ground-based nonuniformity correction.