An Analysis of the Side Slither On-Orbit Calibration Technique Using the DIRSIG Model

Abstract

Pushbroom-style imaging systems exhibit several advantages over line scanners when used on space-borne platforms as they typically achieve higher signal-to-noise and reduce the need for moving parts. Pushbroom sensors contain thousands of detectors, each having a unique radiometric response, which will inevitably lead to streaking and banding in the raw data. To take full advantage of the potential exhibited by pushbroom sensors, a relative radiometric correction must be performed to eliminate pixel-to-pixel non-uniformities in the raw data. Side slither is an on-orbit calibration technique where a 90-degree yaw maneuver is performed over an invariant site to flatten the data. While this technique has been utilized with moderate success for the QuickBird satellite [1] and the RapidEye constellation [2], further analysis is required to enable its implementation for the Landsat 8 sensors, which have a 15-degree field-of-view and a 0.5% pixel-to-pixel uniformity requirement. This work uses the DIRSIG model to analyze the side slither maneuver as applicable to the Landsat sensor. A description of favorable sites, how to adjust the maneuver to compensate for the curvature of "linear" arrays, how to efficiently process the data, and an analysis to assess the quality of the side slither data, are presented.

A Relative Radiometric Calibration Method Based on the Histogram of Side-Slither Data for High-Resolution Optical Satellite Imagery

“…To obtain accurate calibration, data pre-processing is Figure 1 shows the normalization steered viewing mode, in which the same features were not on the same line in the raw side-slither data. To obtain accurate calibration, data pre-processing is essential [16], as it guarantees high-precision relative radiometric coefficients, and ensures that each row has the same features. Figure 4 describes the results of data pre-processing.…”

“…Figure 5 shows the process of basic adjustment using Equation 4. essential [16], as it guarantees high-precision relative radiometric coefficients, and ensures that each row has the same features. Figure 4 describes the results of data pre-processing.…”

“…Due to different along-track and across track samplings [14,15], the same features are not at a line in side-slither data, therefore, pre-processing is required. Instead of the enhanced horizontal correction proposed by [16], this paper introduced line detection to ensure the efficiency and accuracy of calibration data. Then, Otsu's method [17] was used to extract key points that are used for obtaining coefficients.…”

Landsat-8 Sensor Characterization and Calibration

“…Absolute calibration and stability using the on-board calibration devices is covered in the same paper [10] for TIRS, but in detail in a separate paper for OLI (Markham et al,[11]). Analysis of an alternate way to perform detector-to-detector relative radiometric calibration to reduce striping and banding artifacts in imagery is discussed in two papers: Pesta et al [12] which specifically examines OLI and Gerace et al [13], which examines strategies from a more theoretical standpoint using simulations. Validation of the OLI and TIRS radiometric calibrations by using surface measurements, also known as vicarious calibration and by comparison to other instruments, e.g., the Landsat-7 ETM+ is covered in five papers.…”

Vicarious Radiometric Calibration of the Hyperspectral Imaging Microsatellites SPARK-01 and -02 over Dunhuang, China

“…Use of the 90 • yaw observation is efficient for correcting the non-uniform radiometric response among different detectors. This technique has been utilized for Hyperion [9], Quickbird [25], RapidEye [26], and Landsat 8 [27]. Using this technique, all the pixels along the cross-track direction would observe nearly the same scene.…”