Relation between degree of polarization and Pauli color coded image to characterize scattering mechanisms

Maitra, Sanjit; Gartley, Michael; Kerekes, John P.

doi:10.1117/12.918486

Cited by 5 publications

(3 citation statements)

References 7 publications

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“…Fig. 2 shows a simulated PolSAR image with this configuration according to the Pauli decomposition [29]. Figure 3 shows the functions to be maximized as functions of the position for a typical simulation: the likelihood ( Fig.…”

Section: A Precision and Execution Timementioning

confidence: 99%

Comparing Edge Detection Methods Based on Stochastic Entropies and Distances for PolSAR Imagery

Nascimento

Horta

Frery

et al. 2014

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Polarimetric synthetic aperture radar (PolSAR) has achieved a prominent position as a remote imaging method. However, PolSAR images are contaminated by speckle noise due to the coherent illumination employed during the data acquisition. This noise provides a granular aspect to the image, making its processing and analysis (such as in edge detection) hard tasks. This paper discusses seven methods for edge detection in multilook PolSAR images. In all methods, the basic idea consists in detecting transition points in the finest possible strip of data which spans two regions. The edge is contoured using the transitions points and a B-spline curve. Four stochastic distances, two differences of entropies, and the maximum likelihood criterion were used under the scaled complex Wishart distribution; the first six stem from the h-φ class of measures. The performance of the discussed detection methods was quantified and analyzed by the computational time and probability of correct edge detection, with respect to the number of looks, the backscatter matrix as a whole, the SPAN, the covariance an the spatial resolution. The detection procedures were applied to three real PolSAR images. Results provide evidence that the methods based on the Bhattacharyya distance and the difference of Shannon entropies outperform the other techniques.

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Section: A Precision and Execution Timementioning

confidence: 99%

Comparing Edge Detection Methods Based on Stochastic Entropies and Distances for PolSAR Imagery

Nascimento

Horta

Frery

et al. 2014

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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show abstract

“…The true-color imaging method based on encoding stokes parameters has been used to visualize birefringent tissues (e.g., muscles, nerve bundle, and vascular walls) [47]. By encoding multiple polarization-derived parameters (e.g., retardance, depolarization, diattenuation), this method has also been used to extract sample components (e.g., collagen and elastic fibers) [34,66]. In this paper, we implemented the true-color imaging technique based on one parameter, namely the vectorial retardance to enhance the contrast of birefringent microstructures for classifying the three types of skin tissues.…”

Section: Introductionmentioning

confidence: 99%

Distinguishing Malignant Melanoma and Benign Nevus of Human Skin by Retardance Using Mueller Matrix Imaging Polarimeter

Wang

Chen

2023

Applied Sciences

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Malignant melanoma is considered the most serious type of skin cancer. In clinical practice, the conventional technique based on subjective visual examination has a high rate of misdiagnosis for malignant melanoma and benign nevus. Polarization imaging techniques have great potential in clinical diagnosis due to the advantages of improving sensitivity to functional structures, such as microfiber. In this paper, a set of human skin tissue sections, including 853 normal, 851 benign nevus, and 874 malignant melanoma, were analyzed and differentiated using a homemade high-fidelity Mueller matrix imaging polarimeter. The quantitative result using support vector machine algorithms confirmed that, while scalar retardance yields lower accuracy rates, vectorial retardance results in greater accuracy for both the training and testing sets. In particular, the cross-validation accuracy for the training set increased from 88.33% to 98.60%, and the prediction accuracy for the testing set increased from 87.92% to 96.19%. This tackles the limitation of the examination based on clinical experience and suggests that vectorial retardance can provide more accurate diagnostic evidence than scalar retardance. Unfortunately, it is inconvenient and time-consuming to read and analyze each component of the vectorial retardance simultaneously in the qualitative assessment. To address this clinical challenge, a color-encoded vectorial retardance imaging method was implemented. This method can provide superior tissue-specific contrast and more fiber details than scalar retardance. The anisotropic microfiber variation among different skin lesions, including the orientation and distribution, can be clearly highlighted. We believe that this work will not only enable early and rapid diagnosis of skin cancer but also provide a good observation and analysis of the state of cancer progression.

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“…Among the feature differentiated are smoothness, homogeneity, as well as soil moisture, and vegetation discrimination revealed by variation in density and structure. For polarimetric SAR image representation, the Pauli color-coding is a useful application to visually differentiate the three major scattering mechanisms (1) single bounce from a plane surface backscattered towards the radar, (2) double bounce from one flat surface that is horizontal with an adjacent vertical surface, and (3) volume scattering from randomly oriented scatterers [44]. From the original seven UAVSAR bands, Pauli decomposition bands were produced through a linear combination of HH, HV, VH and VV in one three-color RGB image [45] (see Table 3).…”

Section: Datasetmentioning

confidence: 99%

Semi-Automatic Detection of Indigenous Settlement Features on Hispaniola through Remote Sensing Data

et al. 2017

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Satellite imagery has had limited application in the analysis of pre-colonial settlement archaeology in the Caribbean; visible evidence of wooden structures perishes quickly in tropical climates. Only slight topographic modifications remain, typically associated with middens. Nonetheless, surface scatters, as well as the soil characteristics they produce, can serve as quantifiable indicators of an archaeological site, detectable by analyzing remote sensing imagery. A variety of pre-processed, very diverse data sets went through a process of image registration, with the intention to combine multispectral bands to feed two different semi-automatic direct detection algorithms: a posterior probability, and a frequentist approach. Two 5 × 5 km 2 areas in the northwestern Dominican Republic with diverse environments, having sufficient imagery coverage, and a representative number of known indigenous site locations, served each for one approach. Buffers around the locations of known sites, as well as areas with no likely archaeological evidence were used as samples. The resulting maps offer quantifiable statistical outcomes of locations with similar pixel value combinations as the identified sites, indicating higher probability of archaeological evidence. These still very experimental and rather unvalidated trials, as they have not been subsequently groundtruthed, show variable potential of this method in diverse environments.

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Relation between degree of polarization and Pauli color coded image to characterize scattering mechanisms

Cited by 5 publications

References 7 publications

Comparing Edge Detection Methods Based on Stochastic Entropies and Distances for PolSAR Imagery

Comparing Edge Detection Methods Based on Stochastic Entropies and Distances for PolSAR Imagery

Distinguishing Malignant Melanoma and Benign Nevus of Human Skin by Retardance Using Mueller Matrix Imaging Polarimeter

Semi-Automatic Detection of Indigenous Settlement Features on Hispaniola through Remote Sensing Data

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