Dergiler / International Journal of Engineering and Geosciences / 2022 / Cilt: 7 - Sayı: 1

Investigation of the performance of different wavelet-based fusions of SAR and optical images using Sentinel-1 and Sentinel-2 datasets

Sayfa
81–90
Yayın Tarihi
2022-10-19
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

It was seen that the missing regions in the optical images were improved in the fused images with the appropriate wavelet packets and highest SSI.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:In this study, the fusion of optical and synthetic aperture radar images with wavelet transform was investigated.
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Temel Bulgular & Veri:Images are obtained from Sentinel-1 and sentinel-2 satellites.
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Sonuç & Katkı:It was seen that the missing regions in the optical images were improved in the fused images with the appropriate wavelet packets and highest SSI.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Synthetic aperture radar (SAR) · Optical · Wavelet

Abstract

In this study, the fusion of optical and synthetic aperture radar images with wavelet transform was investigated. Images are obtained from Sentinel-1 and sentinel-2 satellites. Images were decomposed by wavelet transform. The four main coefficients were obtained for different wavelet packages and up to ten decomposition levels. The coefficients were combined taking the maximum, minimum or mean. 1710 Fused images were obtained for all possible combinations in terms of different wavelet packets, decomposition levels and fusion rules. Fused images were evaluated according to the structural similarity index (SSI). It was seen that the missing regions in the optical images were improved in the fused images with the appropriate wavelet packets and highest SSI.

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Bu Makaleye Atıf Yap

DUYSAK, H., YİĞİT, E. (2022). Investigation of the performance of different wavelet-based fusions of SAR and optical images using Sentinel-1 and Sentinel-2 datasets. International Journal of Engineering and Geosciences, Cilt: 7 - Sayı: 1, 81–90. https://ajindex.com/articles/540677

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Kaynakça (5)

  1. Aslan M F, Durdu A & Sabanci K (2019). Fusion of CT and MR Liver Images by SURF-Based Registration. International Journal of Intelligent Systems and Applications in Engineering, 7(4), SE-Research Article). doi:10.18201/ijisae.2019457233 Foumelis M, Blasco J M D, Desnos Y, Engdahl M, Fernandez D, Veci L, … Wong C (2018). Esa Snap - Stamps Integrated Processing for Sentinel-1 Persistent Scatterer Interferometry. In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 1364–1367. doi:10.1109/IGARSS.2018.8519545 Ghorbanzadeh O, Didehban K, Rasouli H, Kamran K V, Feizizadeh, B., & Blaschke, T. (2020). An application of sentinel-1, sentinel-2, and GNSS data for landslide susceptibility mapping. ISPRS International Journal of Geo-Information, 9(10), 561. Hemdan E E-D (2021). An efficient and robust watermarking approach based on single value decompression, multi-level DWT, and wavelet fusion with scrambled medical images. Multimedia Tools and Applications, 80(2), 1749–1777. doi:10.1007/s11042-020-09769-7 James A P & Dasarathy B V (2014). Medical image fusion: A survey of the state of the art. Information Fusion, 19, 4–19. doi:https://doi.org/10.1016/j.inffus.2013.12.002
  2. Khaleghi B, Khamis A, Karray F O & Razavi S N (2013). Multisensor data fusion: A review of the state-of-the-art. Information Fusion, 14(1), 28–44. doi:https://doi.org/10.1016/j.inffus.2011.08.001 Kulkarni S C & Rege P P (2020). Pixel level fusion techniques for SAR and optical images: A review. Information Fusion, 59, 13–29. doi:https://doi.org/10.1016/j.inffus.2020.01.003 Pajares G & Manuel de la Cruz J (2004). A wavelet-based image fusion tutorial. Pattern Recognition, 37(9), 1855–1872. doi:https://doi.org/10.1016/j.patcog.2004.03.010
  3. Rajah P, Odindi J & Mutanga O (2018). Feature level image fusion of optical imagery and Synthetic Aperture Radar (SAR) for invasive alien plant species detection and mapping. Remote Sensing Applications: Society and Environment, 10, 198–208. doi:https://doi.org/10.1016/j.rsase.2018.04.007
  4. Shah E, Jayaprasad P & James M E (2019). Image fusion of SAR and optical images for identifying antarctic ice features. Journal of the Indian Society of Remote Sensing, 47(12), 2113–2127.
  5. Veloso A, Mermoz S, Bouvet A, Le Toan T, Planells M, Dejoux J-F & Ceschia E (2017). Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications. Remote Sensing of Environment, 199, 415–426. doi:https://doi.org/10.10