2022
DOI: 10.1038/s41598-022-19088-6
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Polarimetric observables for the enhanced visualization of plant diseases

Abstract: This paper highlights the potential of using polarimetric methods for the inspection of plant diseased tissues. We show how depolarizing observables are a suitable tool for the accurate discrimination between healthy and diseased tissues due to the pathogen infection of plant samples. The analysis is conducted on a set of different plant specimens showing various disease symptoms and infection stages. By means of a complete image Mueller polarimeter, we measure the experimental Mueller matrices of the samples,… Show more

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Cited by 13 publications
(12 citation statements)
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“…In both methods, the construction of the corresponding pseudo-coloring functions is based on the selection of a triplet of polarization-based figures or observables. As previously mentioned, we selected depolarization-related observables because as reported in literature 16 , 17 , 28 30 , and based in our previous experience we know that they are suitable to characterize biological samples 1 , 3 5 . To reinforce this argument, in section 1 of Supplemental document, we show the images of different biological structures related to a representative collection of different polarimetric observables used in the literature, as well as the images corresponding to IPPs and CPs, to show how the latter spaces give rise to greater visual contrast.…”
Section: Resultsmentioning
confidence: 99%
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“…In both methods, the construction of the corresponding pseudo-coloring functions is based on the selection of a triplet of polarization-based figures or observables. As previously mentioned, we selected depolarization-related observables because as reported in literature 16 , 17 , 28 30 , and based in our previous experience we know that they are suitable to characterize biological samples 1 , 3 5 . To reinforce this argument, in section 1 of Supplemental document, we show the images of different biological structures related to a representative collection of different polarimetric observables used in the literature, as well as the images corresponding to IPPs and CPs, to show how the latter spaces give rise to greater visual contrast.…”
Section: Resultsmentioning
confidence: 99%
“…In this work, we have provided optimized pseudo-colored functions based on polarimetric spaces, which enhance other approaches we previously presented in literature 1 , 24 , 25 , 30 . However, we want to note that the application of pseudo-colored functions is not limited to polarimetric spaces 33 36 , and there exist other approaches, as image segmentation and coloring approaches 37 40 , that lead to interesting results in terms of structures visualization.…”
Section: Discussionmentioning
confidence: 99%
“…These four algorithms are described in Section 3 of Supporting information document. This led to 12 final models: (1) ANN with A, (2) ANN with B, (3) ANN with C, (4) SVM with A, (5) SVM with B, (6) SVM with C, (7) LGBM with A, (8) LGBM with B, (9) LGBM with C, (10) XGBoost with A, (11) XGBoost with B, and (12) XGBoost with C.…”
Section: Machine Learning Algorithmsmentioning
confidence: 99%
“…The use of polarization‐based techniques for the study of animal [1, 2], human tissues [3–8] and vegetal samples [9–11] is a well‐stablished field of work which is in constant development [12–14]. Polarimetry comprises a wide range of applications including biomedicine [2], materials characterization [15], atmospheric pollution [16, 17], plant science [10], etc.…”
Section: Introductionmentioning
confidence: 99%
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