English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

. Presence of speckle in the Polarimetric Synthetic Aperture Radar (PolSAR) images could decrease the performance of information extraction applications such as classification, segmentation, change detection, etc. Hence, an essential pre-processing step named de-speckling is needed to suppress this granular noise-like phenomenon from the PolSAR images. In this paper, a comparison study is conducted between several new PolSAR speckle reduction methods such as POSSC, PNGF, and ANLM. For this comparison, a 4-look L-band AIRSAR NASA/JPL PolSAR dataset that obtained over an agriculture land from Flevoland, Netherlands, was employed. The de-speckling assessment was completed based on some no-reference quantitative indicators. All the de-speckling methods were evaluated in terms of speckle reduction form homogeneous areas, details, and radiometric preservation, and retaining the polarimetric information. Furthermore, the impact of PolSAR de-speckling on classification was evaluated. For this purpose, Support Vector Machine (SVM) classifier was used to classify H/A/Alpha decomposition. Experimental results showed that the ANLM method was better to suppress the speckle, followed by the PNGF method. Also, the classification results showed that a proper PolSAR de-speckling could effectively increase the classification accuracy. The improvement of the Overall Accuracy based on de-speckling using the ANLM method was approximately 22% and 13% higher than the POSSC and PNGF methods, respectively.

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

IMPACT OF POLARIMETRIC SAR SPECKLE REDUCTION ON CLASSIFICATION OF AGRICULTURE LANDS