LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Multifrequency Polarimetric SAR Image Despeckling by Iterative Nonlocal Means Based on a Space-Frequency Information Joint Covariance Matrix

Photo from wikipedia

This paper presents an iterative nonlocal means (NLM) filtering method under the Bayesian framework to deal with the issue of multifrequency fully polarimetric synthetic aperture radar (PolSAR) image despeckling. Differing… Click to show full abstract

This paper presents an iterative nonlocal means (NLM) filtering method under the Bayesian framework to deal with the issue of multifrequency fully polarimetric synthetic aperture radar (PolSAR) image despeckling. Differing from most of the PolSAR filters designed for single-frequency data, the proposed NLM method is developed based on a space-frequency information joint covariance matrix, which can not only utilize multifrequency polarimetric information but also exploit the correlation between any two pixels in an image patch. Furthermore, with the aim of accelerating the filtering procedure and better retaining image details, an effective preselection step is employed. The filtering results obtained with both a simulated dataset and real multifrequency PolSAR datasets acquired by the AIRSAR system confirm the good performance of the proposed method in both reducing speckle and retaining details, when compared with some of the state-of-the-art despeckling algorithms.

Keywords: iterative nonlocal; nonlocal means; frequency; image; multifrequency; information

Journal Title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Year Published: 2019

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.