PolSAR Cell Information Representation by a Pair of Elementary Scatterers

Karachristos, Konstantinos; Κούκιου, Γεωργία; Anastassopoulos, V.

doi:10.3390/rs14030695

Cited by 6 publications

(6 citation statements)

References 20 publications

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“…In urban SAR images, the gray-level histogram typically exhibits long tails due to the presence of strong scatterers. These strong scatterers generate exceptionally strong spikes in the images due to dihedral backscattering mechanisms [80], resulting in very high data values. Hence, the initial amplitude floating-point SAR images can be converted into integers with 256 levels prior to performing texture evaluation.…”

Section: Textural Sar Features [2]mentioning

confidence: 99%

SAR Features and Techniques for Urban Planning—A Review

Koukiou

2024

Remote Sensing

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Urban planning has, in recent years, been significantly assisted by remote sensing data. The data and techniques that are used are very diverse and are available to government agencies as well as to private companies that are involved in planning urban and peri-urban areas. Synthetic aperture radar data are particularly important since they provide information on the geometric and electrical characteristics of ground objects and, at the same time, are unaffected by sunlight (day–night) and cloud cover. SAR data are usually combined with optical data (fusion) in order to increase the reliability of the terrain information. Most of the existing relative classification methods have been reviewed. New techniques that have been developed use decorrelation and interferometry to record changes on the Earth’s surface. Texture-based features, such as Markov random fields and co-occurrence matrices, are employed, among others, for terrain classification. Furthermore, target geometrical features are used for the same purpose. Among the innovative works presented in this manuscript are those dealing with tomographic SAR imaging for creating digital elevation models in urban areas. Finally, tomographic techniques and digital elevation models can render three-dimensional representations for a much better understanding of the urban region. The above-mentioned sources of information are integrated into geographic information systems, making them more intelligent. In this work, most of the previous techniques and methods are reviewed, and selected papers are highlighted in order for the reader-researcher to have a complete picture of the use of SAR in urban planning.

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Section: Textural Sar Features [2]mentioning

confidence: 99%

SAR Features and Techniques for Urban Planning—A Review

Koukiou

2024

Remote Sensing

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“…Polarimetric target decompositions, a class of algorithms, have been developed to extract diverse features from PolSAR images, enhancing their utility in classification and target detection tasks by capturing multiple aspects. Many of these algorithms have been proposed in the literature [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33]. These methods can be broadly categorized as either coherent or non-coherent decomposition techniques [18].…”

Section: S =mentioning

confidence: 99%

“…The Entropy-based decomposition introduced by S. R. Cloude and E. Pottier [30], serving as a cornerstone of eigenvector-based decomposition methods, will be discussed in Section 5. Section 6 will analyze the newly established Double Scatterer model approach [33]. A comprehensive evaluation of these techniques will be presented, drawing on experiments conducted using the benchmark Fully Polarimetric dataset covering the broader area of Vancouver.…”

Section: S =mentioning

confidence: 99%

“…To tackle these issues, the methodology presented by the Double Scatterer Model [33] adopts an information extraction approach that aims to explore the information content from both the dominant scattering mechanism and the second most influential scattering mechanism. Specifically, we employ a modification of the geometric topology proposed by Cameron and Rais [22] and introduce a method to represent each PolSAR cell with the two most dominant fundamental scattering mechanisms, along with their respective percentages of contribution or weights.…”

Section: The Double Scatterer Modelmentioning

confidence: 99%

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A Review on PolSAR Decompositions for Feature Extraction

Karachristos,

Koukiou,

Anastassopoulos

2024

J. Imaging

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Feature extraction plays a pivotal role in processing remote sensing datasets, especially in the realm of fully polarimetric data. This review investigates a variety of polarimetric decomposition techniques aimed at extracting comprehensive information from polarimetric imagery. These techniques are categorized as coherent and non-coherent methods, depending on their assumptions about the distribution of information among polarimetric cells. The review explores well-established and innovative approaches in polarimetric decomposition within both categories. It begins with a thorough examination of the foundational Pauli decomposition, a key algorithm in this field. Within the coherent category, the Cameron target decomposition is extensively explored, shedding light on its underlying principles. Transitioning to the non-coherent domain, the review investigates the Freeman–Durden decomposition and its extension, the Yamaguchi’s approach. Additionally, the widely recognized eigenvector–eigenvalue decomposition introduced by Cloude and Pottier is scrutinized. Furthermore, each method undergoes experimental testing on the benchmark dataset of the broader Vancouver area, offering a robust analysis of their efficacy. The primary objective of this review is to systematically present well-established polarimetric decomposition algorithms, elucidating the underlying mathematical foundations of each. The aim is to facilitate a profound understanding of these approaches, coupled with insights into potential combinations for diverse applications.

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“…A detailed representation of the contribution of each scattering mechanism in the four basic land cover types is given in Table 4 [ 33 ]. The region with the “smoothest” scattering surface, the Water area, has a reddish color.…”

Section: Experimental Approach and Color Relevance To Scattering Mech...mentioning

confidence: 99%

Perceptually Optimal Color Representation of Fully Polarimetric SAR Imagery

Κούκιου¹

2022

J. Imaging

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The four bands of fully polarimetric SAR data convey scattering characteristics of the Earth’s background, but perceptually are not very easy for an observer to use. In this work, the four different channels of fully polarimetric SAR images, namely HH, HV, VH, and VV, are combined so that a color image of the Earth’s background is derived that is perceptually excellent for the human eye and at the same time provides accurate information regarding the scattering mechanisms in each pixel. Most of the elementary scattering mechanisms are related to specific color and land cover types. The innovative nature of the proposed approach is due to the two different consecutive coloring procedures. The first one is a fusion procedure that moves all the information contained in the four polarimetric channels into three derived RGB bands. This is achieved by means of Cholesky decomposition and brings to the RGB output the correlation properties of a natural color image. The second procedure moves the color information of the RGB image to the CIELab color space, which is perceptually uniform. The color information is then evenly distributed by means of color equalization in the CIELab color space. After that, the inverse procedure to obtain the final RGB image is performed. These two procedures bring the PolSAR information regarding the scattering mechanisms on the Earth’s surface onto a meaningful color image, the appearance of which is close to Google Earth maps. Simultaneously, they give better color correspondence to various land cover types compared with existing SAR color representation methods.

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PolSAR Cell Information Representation by a Pair of Elementary Scatterers

Cited by 6 publications

References 20 publications

SAR Features and Techniques for Urban Planning—A Review

SAR Features and Techniques for Urban Planning—A Review

A Review on PolSAR Decompositions for Feature Extraction

Perceptually Optimal Color Representation of Fully Polarimetric SAR Imagery

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