Abstract
Introduction. A radar image is an image obtained by remote sensing the earth's surface with a radar device. Radar images are characterized by background graininess caused by speckle noise, which should be filtered to improve the quality of radar images. The structure of speckle noise reduction filters often comprise one or more parameters to control the level of noise smoothing. The values of these parameters have to be selected experimentally. In works devoted to speckle noise filtering, the methods used for selecting filter paraments are rarely clarified.Aim. To present a methodology for selecting the parameters of multiplicative speckle noise filters on a radar image that are optimal in terms of the quality of the resulting image.Materials and methods. The article presents a method for determining the optimal parameters of speckle noise reduction filters. This method was applied to the most conventionally used filters. The search for optimal parameters and testing of the filters were carried out using a specially designed image, which contained the objects most frequently found on radar images. The structural similarity index (SSIM) metric was chosen as a metric that assesses the quality of filtration.Results. After determining the optimal (in terms of SSIM) parameters of speckle noise reduction filters, the filters were compared to select the best filters in terms of the quality of radar image processing. In addition, the operation of the filters under study was tested on images containing various types of objects, namely: large objects, small objects and sharp borders. Knowing which filter copes best with smoothing speckle noise in a particular area and what values of the variable parameters this requires, an optimal quality of radar images can be achieved. Filtering not only improves human perception of radar images, but also reduces the influence of speckle noise during their further processing (object detection, segmentation of areas, etc.).Conclusion. The proposed algorithm allowed optimal parameters for several speckle noise filters to be determined. The quality of filtration was assessed using an expert method (visually) by comparing images before and after filtration, differential images and one-dimensional image slices. The Frost filter and the anisotropic diffusion filter with optimal parameters showed the best processing quality according to the SSIM metric.
Highlights
A radar image is an image obtained by remote sensing the earth's surface with a radar device
On the criterion that a given system of deviations from theprobable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling // Breakthroughs in Statistics: Methodology and Distribution
Filters // Internet of Things, Smart Spaces and Generation Networks and Systems, Springer Intern
Summary
Imagery / Jong-Sen Lee, Jen-Hung Wen, T. J. Chen // IEEE Transactions on Geoscience and Remote Sensing. FPGA-Based Adaptive Speckle Suppression Filter for Underwater Imaging Sonar / S. Spatial filtering strategies on deforestation detection using SAR image textures / X. Anisotropic Diffusion Filter With Memory Based on Speckle Statistics for Ultrasound Images / G. Aja-Fernández // IEEE Transactions on Image Processing. T. Speckle Removal Using Diffusion Potential for Optical Coherence Tomography Images // IEEE J Biomed Health Inform. Addison-Wesley Longman Publishing Co., Inc., USA, New Jersey 07458, 2001. 191 p
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