155
Views
2
CrossRef citations to date
0
Altmetric
Articles

Revisiting the effect of spatial resolution on information content based on classification results

ORCID Icon, & ORCID Icon
Pages 4489-4505 | Received 04 May 2018, Accepted 09 Aug 2018, Published online: 25 Jan 2019

References

  • Aghababaee, H., J. Amini, and Y. Chang Tzeng. 2013. “Contextual PolSAR Image Classification Using Fractal Dimension and Support Vector Machines.” European Journal of Remote Sensing 46 (1): 317–332. doi:10.5721/EuJRS20134618.
  • Argenti, F., A. Lapini, T. Bianchi, and L. Alparone. 2013. “A Tutorial on Speckle Reduction in Synthetic Aperture Radar Images.” IEEE Geoscience and Remote Sensing Magazine 1 (3): 6–35. doi:10.1109/MGRS.2013.2277512.
  • Burges, C. 1998. “A Tutorial on Support Vector Machines for Pattern Recognition.” Data Mining and Knowledge Discovery 2 (2): 121–167. doi:10.1023/A:1009715923555.
  • Foucher, S., and C. López-Martínez. 2014. “Analysis, Evaluation, and Comparison of Polarimetric SAR Speckle Filtering Techniques.” IEEE Transactions on Image Processing 23 (4): 1751–1764. doi:10.1109/TIP.2014.2307437.
  • Freeman, A., and S. L. Durden. 1998. “A Three-Component Scattering Model for Polarimetric SAR Data.” IEEE Transactions on Geoscience and Remote Sensing 36 (3): 963–973. doi:10.1109/36.673687.
  • Frery, A. C., A. D. C. Nascimento, and R. J. Cintra. 2014. “Analytic Expressions for Stochastic Distances between Relaxed Complex Wishart Distributions.” IEEE Transactions on Geoscience and Remote Sensing 52 (2): 1213–1226. doi:10.1109/TGRS.2013.2248737.
  • Harris Geospatial Solutions. 2018. ENVI – Environment for Visualizing Images. https://www.harrisgeospatial.com/docs/using_envi_Home.html
  • Helmy, A. K., and G. S. El-Taweel. 2016. “Adaptive Local Means Filter for Polarimetric SAR Images; Despeckling for Homogeneous and Heterogeneous Clutter Models.” Information Technology and Computer Science 11: 33–45. doi:10.5815/ijitcs.2016.11.05.
  • Huang, Y., G. Liao, Z. Zhang, Y. Xiang, J. Li, and A. Nehorai. 2018. “SAR Automatic Target Recognition Using Joint Low-Rank and Sparse Multiview Denoising.” IEEE Geoscience and Remote Sensing Letters  15 (10): 1570-1574. https://doi.org/10.1080/17538947.2018.1474958.
  • Lardeux, C., P. Frison, C. Tison, J. C. Souyris, B. Stoll, B. Fruneau, and J. P. Rudant. 2009. “Support Vector Machine for Multifrequency SAR Polarimetric Data Classification.” IEEE Transactions on Geoscience and Remote Sensing 47 (12): 4143–4152. doi:10.1109/TGRS.2009.2023908.
  • Lee, J. S. 1980. “Digital Image Enhancement and Noise Filtering by Use of Local Statistics.” IEEE Transactions on Pattern Analysis and Machine Intelligence 2: 165–168. doi:10.1109/TPAMI.1980.4766994.
  • Lee, J. S., M. R. Grunes, and G. de Grandi. 1999. “Polarimetric SAR Speckle Filtering and Its Implication for Classification.” IEEE Transactions on Geoscience and Remote Sensing 37 (5): 2363–2373. doi:10.1109/36.789635.
  • López-Martínez, C., and E. Pottier. 2007. “Coherence Estimation in Synthetic Aperture Radar Data Based on Speckle Noise Modeling.” Applied Optics 46 (4): 544–558. doi:10.1364/AO.46.000544.
  • López-Martnez, C., and X. Fàbregas. 2003. “Polarimetric SAR Speckle Noise Model.” IEEE Transactions on Geoscience and Remote Sensing 41 (10): 2232–2242. doi:10.1109/TGRS.2003.815240.
  • López-Martnez, C., and X. Fàbregas. 2008. “Model-Based Polarimetric SAR Speckle Filter.” IEEE Transactions on Geoscience and Remote Sensing 46 (11): 3894–3907. doi:10.1109/TGRS.2008.2002029.
  • Ma, X., H. Shen, Q. Yuan, and L. Zhang. 2014. “Spatially Adaptive Nonlocal Total Variation for PolSAR Despeckling.” In 2014 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2014, 1670–1676 Quebec City, QC. doi:10.1109/IGARSS.2014.6946770.
  • Ma, X., H. Shen, and L. Zhang. 2016. “PolSAR Anisotropic Diffusion Filter with a Refined Similarity Measure and an Adaptive Fidelity Constraint.” International Journal of Remote Sensing 37 (24): 5988–6011. doi:10.1080/01431161.2016.1253893.
  • Maselli, F., C. Conese, L. Petkov, and R. Resti. 1992. “Inclusion of Prior Probabilities Derived from a Nonparametric Process into the Maximum Likelihood Classifier.” Photogrammetric Engineering and Remote Sensing 58: 201–207.
  • Maulik, U., and D. Chakraborty. 2017. “Remote Sensing Image Classification: A Survey of Support-Vector-Machine-Based Advanced Techniques.” IEEE Geoscience and Remote Sensing Magazine 5 (1): 33–52. doi:10.1109/MGRS.2016.2641240.
  • Medasani, S., and G. Umamaheswara Reddy. 2017. “Analysis and Evaluation of Speckle Filters for Polarimetric Synthetic Aperture Radar (PoLSAR) Data.” International Journal of Applied Engineering Research 12 (15): 4916–4927.
  • Narayanan, R. M., M. K. Desetty, and S. E. Reichenbach. 2002. “Effect of Spatial Resolution on Information Content Characterization in Remote Sensing Imagery Based on Classification Accuracy.” International Journal of Remote Sensing 23 (3): 537–553. doi:10.1080/01431160010025970.
  • Negri, R. G., A. C. Frery, W. B. Silva, T. S. G. Mendes, and L. V. Dutra. 2018. “Region-Based Classification of PolSAR Data Using Radial Basis Kernel Functions with Stochastic Distances.” International Journal of Digital Earth.
  • Palacio, M. G., S. B. Ferrero, and A. C. Frery. 2017. “Information Content in SAR Images: A Classification Accuracy Viewpoint.” In 2017 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017, 5307–5310. Fort Worth, TX. doi:10.1109/IGARSS.2017.8128202.
  • Pottier, E., and L. Ferro-Famil. 2012. “PolSARPro V5.0: An ESA Educational Toolbox Used for Self-Education in the Field of POLSAR and POL-INSAR Data Analysis.” In 2012 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012, 7377–7380.
  • R Core Team. 2018. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/
  • Strahler, A. H. 1980. “The Use of Prior Probabilities in Maximum Likelihood Classification of Remotely Sensed Data.” Remote Sensing of Environment 10: 135–163. doi:10.1016/0034-4257(80)90011-5.
  • Torres, L., S. J. S. Sant’Anna, C. Da Costa Freitas, and A. C. Frery. 2014. “Speckle Reduction in Polarimetric SAR Imagery with Stochastic Distances and Nonlocal Means.” Pattern Recogn 47 (1): 141–157. doi:10.1016/j.patcog.2013.04.001.
  • Vapnik, V. N. 1995. The Nature of Statistical Learning Theory. New York, NY: Springer-Verlag New York.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.