FAST AND ACCURATE MULTI-FRAME SUPER-RESOLUTION OF SATELLITE IMAGES

Author:

Anger J.,Ehret T.,de Franchis C.,Facciolo G.

Abstract

Abstract. Recent constellations of small satellites, such as Planet’s SkySats, offer new acquisition modes where very short videos or bursts of images are acquired instead of a single still image. Compared to sequences of multi-date images, these sequences of consecutive video frames yield a large redundancy of information within the range of seconds. This redundancy enables to increase the spatial resolution using multi-frame super-resolution algorithms. In this paper, we propose a novel super-resolution method based on a high-order spline interpolation model that combines multiple low-resolution frames to produce a high-resolution image. Moreover this method can be implemented efficiently on GPU to process entire images from real satellite acquisitions. Synthetic and real experiments show that the proposed method is able to recover fine details, and measurements of the resulting resolution indicate a gain of 10 cm / pixel with respect to Planet’s SkySat standard imagery products.

Publisher

Copernicus GmbH

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. MCDNet: Multi Context Dense Network for multi-frame super resolution of satellite images;Proceedings of the Fourteenth Indian Conference on Computer Vision, Graphics and Image Processing;2023-12-15

2. Super-resolution biomedical imaging via reference-free statistical implicit neural representation;Physics in Medicine & Biology;2023-10-16

3. Handheld Burst Super-Resolution Meets Multi-Exposure Satellite Imagery;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW);2023-06

4. L1BSR: Exploiting Detector Overlap for Self-Supervised Single-Image Super-Resolution of Sentinel-2 L1B Imagery;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW);2023-06

5. Blind Superresolution of Satellite Videos by Ghost Module-Based Convolutional Networks;IEEE Transactions on Geoscience and Remote Sensing;2023

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