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A novel country-level integrated image mosaic system using optical remote sensing imagery

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Abstract

Remote sensing image mosaicking is an essential processing step in generating large area coverage map using multi-temporal image scenes/strips. The mosaic data is useful for various space-borne applications that span across national level crop assessment, wetland monitoring, and snow and glacier studies, to derive important environmental indicators for sustainable development. This article highlights a novel image mosaicking processing workflow that ingests input geo-referenced image strips with sufficient overlap in-between, and generates country-level mosaic data product. The procedure takes care of large-sized geo-referenced image’s handling and re-projection, and makes data ready for mosaic processing. We have developed strip geo-registration method using Scale Invariant Feature Transform (SIFT) and Mode Biased Random Sample Consensus (MB-RANSAC) outlier removal technique to achieve sub-pixel registration accuracy. Image stitching workflow ingests co-registered image strips, and performs overlap extraction, seamline detection using multi-frame joint strategy, and image blending using region-based statistics in an automatic manner. The mosaic system has been evaluated with Resourcesat’s medium resolution optical remote sensing images over Indian subcontinent, and it has been confirmed that the common region among image strips attains required radiometric and geometric fidelity after correction. It also has been found that the average spectra deviation is less than 0.127% at different classes.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  • Alcantarilla PF, Solutions T (2011) Fast explicit diffusion for accelerated features in nonlinear scale spaces. IEEE Trans Pattern Anal Mach Intell 34(7):1281–1298

    Google Scholar 

  • Asokan A, Anitha JJESI (2019) Change detection techniques for remote sensing applications: a survey. Earth Sci Inf 12(2):143–160

    Article  Google Scholar 

  • Atik ME, Ozturk O, Duran Z, Seker DZ (2020) An automatic image matching algorithm based on thin plate splines. Earth Sci Inf 13(3):869–882

    Article  Google Scholar 

  • Bay H, Tuytelaars T, Gool LV (2011) "Surf: Speeded up robust features," In Eur Conference on Comput Vision, pp. 404–417. Springer, Berlin, Heidelberg

  • Barath D, Matas J, Noskova J (2019) "MAGSAC: marginalizing sample consensus." In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 10197–10205

  • Chum O, Matas J (2005) "Matching with PROSAC-progressive sample consensus," In IEEE Comput Soc Conference Comput Vision Pattern Recognition (CVPR'05), vol. 1, pp. 220–226

  • Chum O, Matas J, Kittler J (2003) "Locally optimized RANSAC," In J Pattern Recognition Symp, pp. 236–243. Springer, Berlin, Heidelberg

  • Dijkstra EW (1959) A note on two problems in connexion with graphs. Numerische Mathematic 1(1):269–271

    Article  Google Scholar 

  • Duplaquet M (1998) Building large image mosaics with invisible seam lines. In Visual Inf Process VII 3387:369–377 (SPIE)

    Google Scholar 

  • Du Q, Raksuntorn N, Orduyilmaz A, Bruce LM (2008) Automatic registration and mosaicking for airborne multispectral image sequences. Photogramm Eng Remote Sens 74(2):169–181

    Article  Google Scholar 

  • Edwards CS, Nowicki KJ, Christensen PR, Hill J, Gorelick N, Murray K (2011) Mosaicking of global planetary image datasets: Techniques and data processing for Thermal Emission Imaging System (THEMIS) multi‐spectral data. J Geo-Phys Res 116

  • Fernandez E, Garfinkel R, Arbiol R (1998) Mosaicking of aerial photographic maps via seams defined by bottleneck shortest paths. Oper Res 46(3):293–304

    Article  Google Scholar 

  • Fischler MA, Bolles RC (1981) Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. ACM Commun 24(6):381–395

    Article  Google Scholar 

  • Greig MD, Porteous BT, Seheult AH (1989) Exact maximum a posteriori estimation for binary images. J Roy Stat Soc: Ser B (methodol) 51(2):271–279

    Google Scholar 

  • Goncalves H, Corte-Real L, Goncalves JA (2011) Automatic image registration through image segmentation and SIFT. IEEE Trans Geosci Remote Sens 49(7):2589–2600

    Article  Google Scholar 

  • Guo M, Li J, Sheng C, Xu J, Wu L (2017) A review of wetland remote sensing. Sensors 17:4

    Google Scholar 

  • Hua Z, Li Y, Li J (2010) Image stitch algorithm based on SIFT and MVSC. In 2010 Seventh IEEE Int Conference on Fuzzy Syst Knowledge Discovery 6:2628–2632

    Article  Google Scholar 

  • Hong D, Gao L, Yokoya N, Yao J, Chanussot J, Du Q, Zhang B (2020a) More diverse means better: Multimodal deep learning meets remote-sensing imagery classification. IEEE Trans Geosci Remote Sens 59(5):4340–4354

    Article  Google Scholar 

  • Hong D, Gao L, Yao J, Zhang B, Plaza A, Chanussot J (2020b) Graph convolutional networks for hyperspectral image classification. IEEE Trans Geosci Remote Sens 59(7):5966–5978

    Article  Google Scholar 

  • Kass M, Witkin A, Terzopoulos D (1988) Snakes: Active contour models. Int J Comput Vision 1(4):321–331

    Article  Google Scholar 

  • Kim D, Yoon Y, Choi JS (2003) An efficient method to build panoramic image mosaics. Pattern Recogn Lett 24(14):2421–2429

    Article  Google Scholar 

  • Kupfer B, Netanyahu NS, Shimshoni I (2014) An efficient SIFT-based mode-seeking algorithm for sub-pixel registration of remotely sensed images. IEEE Geosci Remote Sens Lett 12(2):379–383

    Article  Google Scholar 

  • Levin A, Zomet A, Peleg S, Weiss Y (2004) "Seamless image stitching in the gradient domain." In Eur Conference Comput Vision, pp. 377–389. Springer, Berlin, Heidelberg

  • Li X, Hui N, Shen H, Fu Y, Zhang L (2015) A robust mosaicking procedure for high spatial resolution remote sensing images. ISPRS J Photogramm Remote Sens 109:108–125

    Article  Google Scholar 

  • Li L, Yao J, Lu X, Tu J, Shan J (2016) Optimal seamline detection for multiple image mosaicking via graph cuts. ISPRS J Photogramm Remote Sens 113:1–16

    Article  Google Scholar 

  • Li L, Yao J, Xie R, Li J (2018) Edge-enhanced optimal seamline detection for orthoimage mosaicking. IEEE Geosci Remote Sens Lett 15(5):764–768

    Article  Google Scholar 

  • Li X, Feng R, Guan X, Shen H, Zhang L (2019) Remote sensing image mosaicking: Achievements and challenges. IEEE Geosci Remote Sens Magazine 7(4):8–22

    Article  Google Scholar 

  • Lowe DG (1999) Object recognition from local scale-invariant features. In Proceed Seventh IEEE Int Conference on Comput Vision 2:1150–1157

    Article  Google Scholar 

  • Misra I, Moorthi SM, Dhar D, Ramakrishnan R (2012) "An automatic satellite image registration technique based on Harris corner detection and Random Sample Consensus (RANSAC) outlier rejection model," In 2012 1st IEEE Int Conference Recent Adv Inf Technol (RAIT), pp. 68–73

  • Misra I, Moorthi SM, Sharma V, Sangar G, Dhar D (2016) "Full India NDVI map generation using Resourcesat-2 AWiFS data." Space Applications Centre, ISRO

  • Misra I, Sharma V, Moorthi SM, Dhar D (2018) "An Automated Approach For Reference Image Generation Using Multi-Tier Resourcesat-2a Data Over Indian Land Terrain," In 38th INCA International Congress

  • Misra I, Sharma V, Moorthi SM, Dhar D (2019a) An approach for generation of multi temporal co-registered optical remote sensing images from Resourcesat-2/2A sensors. Journal of Geomatics 13(1):173–178

  • Misra I, Moorthi SM, Dhar D (2019b) Techniques Developed for Large Area Mars Image Mosaic using ISRO’s Mars Color Camera (MCC) Data. Indian J Geomatics 13(1):174–179

  • Misra I, Rohil MK, Moorthi SM, Dhar D (2021a) FIRM: Framework for Image Registration Using Multistage Feature Detection and Mode-Guided Motion Smoothness Keypoint Optimization. IEEE Trans Geosci Remote Sens 60:1–12

  • Misra I, Rout L, Arya S, Bhateja Y, Moorthi SM, Dhar D (2021b) Phobos image enhancement using unpaired multi-frame acquisitions from Indian Mars Color Camera. Planet Space Sci 201:105215

  • Mills S, McLeod P (2013) Global seamline networks for orthomosaic generation via local search. ISPRS J Photogramm Remote Sens 75:101–111

    Article  Google Scholar 

  • Pan J, Fang Z, Chen S, Ge H, Hu F, Wang M (2018) An improved seeded region growing-based seamline network generation method. Remote Sens 10:7

    Article  Google Scholar 

  • Resourcesat-2 Data User’s Handbook (2011) 1st Ed., National Remote Sensing Centre (NRSC), ISRO, India, pp. 1–142

  • Rublee E, Rabaud V, Konolige K, Bradski G (2011) "ORB: An efficient alternative to SIFT or SURF," IEEE Int Conference on Comput Vision, pp. 2564–2571

  • Rusia P, Bhateja Y, Misra I, Moorthi SM, Dhar D (2021) An Efficient Machine Learning Approach for Atmospheric Correction. J Indian Soc Remote Sens 49(10):2539–2548

    Article  Google Scholar 

  • Saxena S, Rabha A, Tahlani P, Ray SS (2021) Crop situation in India, before, during and after COVID-19 lockdown, as seen from the satellite data of resourcesat-2 AWiFS. J Indian Soc Remote Sens 49(2):365–376

    Article  Google Scholar 

  • Snyder J (1982) “Map projections used by the US Geological Survey”, no. 1532, US Government Printing Office

  • Torr P, Zisserman A (1998) "Robust computation and parametrization of multiple view relations," In Sixth IEEE Int Conference Comput Vision , pp. 727–732, 1998.

  • Vermote EF, Tanré D, Deuze JL, Herman M, Morcette JJ (1997) Second simulation of the satellite signal in the solar spectrum, 6S: An overview. IEEE Trans Geosci Remote Sens 35(3):675–686

    Article  Google Scholar 

  • Wang B, Li H, Hu W (2020) Research on key techniques of multi-resolution coastline image fusion based on optimal seam-line. Earth Sci Inf 13(2):333–344

    Article  Google Scholar 

  • Whitaker RT (2000) A level-set approach to image blending. IEEE Trans Image Process 9(11):1849–1861

    Article  Google Scholar 

  • Wu X, Hong D, Chanussot J (2021) Convolutional neural networks for multimodal remote sensing data classification. IEEE Trans Geosci Remote Sens 60:1–10

    Article  Google Scholar 

  • Yang Z, Kang Z, Yang J (2020) A Semiautomatic Registration Method for Chang’E-1 IIM Imagery Based on Globally Geo-Reference LROC-WAC Mosaic Imagery. IEEE Geosci Remote Sens Lett 18(3):543–547

    Article  Google Scholar 

Download references

Acknowledgements

The authors thank Director, Space Applications Centre, ISRO, Ahmedabad, India for his encouragement and support. The authors also acknowledge all members of Signal and Image Processing Group, Space Applications Centre, ISRO, Ahmedabad, India for their suggestions regarding the country-level mosaic data product.

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Authors and Affiliations

  1. Signal and Image Processing Group, Space Applications Centre, Indian Space Research Organisation (ISRO), Ahmedabad, Gujarat, India

    Indranil Misra, S. Manthira Moorthi & Debajyoti Dhar

  2. Department of Computer Science and Information Systems, Birla Institute of Technology and Science, Pilani, Rajasthan, India

    Mukesh Kumar Rohil

Authors
  1. Indranil Misra
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  2. Mukesh Kumar Rohil
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  3. S. Manthira Moorthi
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  4. Debajyoti Dhar
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Contributions

IM: Conceptualization, Methodology, Software and Writing: Original Draft Preparation.

MKR: Conceptualization, Formal Analysis, Review and Editing.

SMM: Conceptualization, Formal Analysis, Review and Editing.

DD: Resources, Supervision, Review and Editing.

All authors read and approved the final manuscript.

Corresponding author

Correspondence to Indranil Misra.

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The authors declare no competing interests.

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The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Communicated by: H. Babaie

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Misra, I., Rohil, M.K., Moorthi, S. et al. A novel country-level integrated image mosaic system using optical remote sensing imagery. Earth Sci Inform 15, 2181–2193 (2022). https://doi.org/10.1007/s12145-022-00865-w

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