Resolution-Normalizing Image Stitching for Long-Linear-Array and Wide-Swath Whiskbroom Payloads

Abstract

Affected by the large and inconsistent geometric distortion deriving from long-linear-array and wide-swath whiskbroom (LWW) imaging and the small overlap area of adjacent images, the conventional stitching methods based on feature matching greatly suffer from the severe misalignment, ghosting effect and distortion in overlapping and non-overlapping areas, respectively. Here, in view of these problems, this letter proposes a resolution-normalizing stitching method for LWW images. Firstly, considering the variation of scan-angle, earth curvature, and pixel position along-track, we establish a resolution characterization model to calculate the accurate ground sampling distance (GSD) anywhere in the field of view. Then, accordingly, the resolution-normalizing method comprising GSD allocation and gray-value interpolation is proposed to re-project the original adjacent images for eliminating the resolution inconsistency along-track. Finally, the normalized images were stitched based on the perspective transformation with matching corresponding pairs. Experimental results evaluated on the images of Thermal Infrared Spectrometer (TIS) aboard Sustainable Development Goals Satellite-1 (SDGSAT-1) show that the stitching accuracy of the proposed method can be around 0.5 pixels, and more importantly, the ghosting effects and projection distortions are reduced effectively.