In this work we present a novel benchmarking framework for assessing the quality of despeckled multitemporal SAR images on an objective basis. Taking cues from a recent work providing a useful tool for measuring the performance of single-channel despeckling filters, here we extend that analysis to multitemporal filters and datasets. Due to the lack of reference speckle-free real SAR images, the quantitative performance parameters introduced here are evaluated on simulated time series of canonical scenes obtained through a reliable and well-assessed SAR simulator which accounts for both geometrical and electromagnetic properties of the scattering surface. First we analyze image quality over datasets with homogeneous reflectivity in time. Then, for a more realistic performance assessment in practical situations, ad-hoc quality parameters are introduced to measure the effects of time-varying scene characteristics on the despeckled dataset. The consistency of the proposed framework is tested on state-of-the-art multitemporal despeckling algorithms.

Assessing Performance of Multitemporal SAR Image Despeckling Filters via a Benchmarking Tool / Di Martino, G.; Di Simone, A.; Iodice, A.; Riccio, D.; Ruello, G.. - (2020), pp. 1536-1539. (Intervento presentato al convegno 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 tenutosi a usa nel 2020) [10.1109/IGARSS39084.2020.9323137].

Assessing Performance of Multitemporal SAR Image Despeckling Filters via a Benchmarking Tool

Di Martino G.;Di Simone A.;Iodice A.;Riccio D.;Ruello G.
2020

Abstract

In this work we present a novel benchmarking framework for assessing the quality of despeckled multitemporal SAR images on an objective basis. Taking cues from a recent work providing a useful tool for measuring the performance of single-channel despeckling filters, here we extend that analysis to multitemporal filters and datasets. Due to the lack of reference speckle-free real SAR images, the quantitative performance parameters introduced here are evaluated on simulated time series of canonical scenes obtained through a reliable and well-assessed SAR simulator which accounts for both geometrical and electromagnetic properties of the scattering surface. First we analyze image quality over datasets with homogeneous reflectivity in time. Then, for a more realistic performance assessment in practical situations, ad-hoc quality parameters are introduced to measure the effects of time-varying scene characteristics on the despeckled dataset. The consistency of the proposed framework is tested on state-of-the-art multitemporal despeckling algorithms.
2020
978-1-7281-6374-1
Assessing Performance of Multitemporal SAR Image Despeckling Filters via a Benchmarking Tool / Di Martino, G.; Di Simone, A.; Iodice, A.; Riccio, D.; Ruello, G.. - (2020), pp. 1536-1539. (Intervento presentato al convegno 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 tenutosi a usa nel 2020) [10.1109/IGARSS39084.2020.9323137].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/856625
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