It is well known that remote sensed scenes could be affected by many factors and, for optimum change detection, these unwanted effects must be removed. In this study a new algorithm is proposed for PIF (Pseudo Invariant Features) extraction and relative radiometric normalization. The new algorithm can be labeled as a supervised one and combines three methods for the detection of PIFs: Moment distance index (MDI), Normalized Difference Vegetation Index (NDVI) masks morphological erosion and dilate operators. In order to prove its effectiveness, the algorithm was tested by using Landsat 8 scenes of the “Mar de Plstico” landscape of the Andalusian Almería. Many tests were performed in order to provide a set of valid input parameters for the chosen environments. Lastly, the results were statistically assessed with parametric and non-parametric tests showing very good and stable results in the four different study areas.
A new threshold relative radiometric correction algorithm (TRRCA) of multiband satellite data / Novelli, Antonio; Aguilar, Manuel A.; Tarantino, Eufemia (SMART INNOVATION, SYSTEMS AND TECHNOLOGIES). - In: Intelligent interactive multimedia systems and services 2017 / [a cura di] Giuseppe De Pietro, Luigi Gallo, Robert J. Howlett, Lakhmi C. Jain. - ELETTRONICO. - Cham, CH : Springer, 2018. - ISBN 978-3-319-59479-8. - pp. 41-50 [10.1007/978-3-319-59480-4_5]
A new threshold relative radiometric correction algorithm (TRRCA) of multiband satellite data
NOVELLI, Antonio;TARANTINO, Eufemia
2018-01-01
Abstract
It is well known that remote sensed scenes could be affected by many factors and, for optimum change detection, these unwanted effects must be removed. In this study a new algorithm is proposed for PIF (Pseudo Invariant Features) extraction and relative radiometric normalization. The new algorithm can be labeled as a supervised one and combines three methods for the detection of PIFs: Moment distance index (MDI), Normalized Difference Vegetation Index (NDVI) masks morphological erosion and dilate operators. In order to prove its effectiveness, the algorithm was tested by using Landsat 8 scenes of the “Mar de Plstico” landscape of the Andalusian Almería. Many tests were performed in order to provide a set of valid input parameters for the chosen environments. Lastly, the results were statistically assessed with parametric and non-parametric tests showing very good and stable results in the four different study areas.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
