Abstract

Abstract. Continuous and automated co-registration and geo-tagging of images from multiple bands of Liss-4 camera is one of the interesting challenges of Resourcesat-2 data processing. Three arrays of the Liss-4 camera are physically separated in the focal plane in alongtrack direction. Thus, same line on the ground will be imaged by extreme bands with a time interval of as much as 2.1 seconds. During this time, the satellite would have covered a distance of about 14 km on the ground and the earth would have rotated through an angle of 30”. A yaw steering is done to compensate the earth rotation effects, thus ensuring a first level registration between the bands. But this will not do a perfect co-registration because of the attitude fluctuations, satellite movement, terrain topography, PSM steering and small variations in the angular placement of the CCD lines (from the pre-launch values) in the focal plane. This paper describes an algorithm based on the viewing geometry of the satellite to do an automatic band to band registration of Liss-4 MX image of Resourcesat-2 in Level 1A. The algorithm is using the principles of photogrammetric collinearity equations. The model employs an orbit trajectory and attitude fitting with polynomials. Then, a direct geo-referencing with a global DEM with which every pixel in the middle band is mapped to a particular position on the surface of the earth with the given attitude. Attitude is estimated by interpolating measurement data obtained from star sensors and gyros, which are sampled at low frequency. When the sampling rate of attitude information is low compared to the frequency of jitter or micro-vibration, images processed by geometric correction suffer from distortion. Therefore, a set of conjugate points are identified between the bands to perform a relative attitude error estimation and correction which will ensure the internal accuracy and co-registration of bands. Accurate calculation of the exterior orientation parameters with GCPs is not required. Instead, the relative line of sight vector of each detector in different bands in relation to the payload is addressed. With this method a band to band registration accuracy of better than 0.3 pixels could be achieved even in high hill areas.

Highlights

  • Resourcesat-2 (RS-2) ground segment is fully operational since on-orbit acceptance (October 2011)

  • Co-registration and in-flight calibration updates of MISR (Multi-angle Imaging Spectro Radiometer) imagery is explained by Jovanovic, 2002

  • This is necessary to update the information on satellite position and orientation which is acquired by satellite navigation system during image acquisition with the help of image itself which provides the measure of misregistration visually

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Summary

INTRODUCTION

Resourcesat-2 (RS-2) ground segment is fully operational since on-orbit acceptance (October 2011) This satellite is intended to continue the remote sensing data services to global users provided by IRS-P6 (RS-1) with enhanced performance. Theiler et al, 2002, explain automated coregistration of Multi spectral Thermal Imager (MTI) bands using photogrammetric methods They have reported the automated image registration of MTI imagery through entirely image-based methods. To do this, viewing geometry and inter image relation is exploited by means of image matching but in very limited way unlike total image based registration method This is necessary to update the information on satellite position and orientation which is acquired by satellite navigation system during image acquisition with the help of image itself which provides the measure of misregistration visually. The resulted co-registered products will be orbit aligned and is ready for further processing

Elevation effects
Test Data
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