scholarly journals Comparison of Imaging Models for Spectral Unmixing in Oil Painting

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2471
Author(s):  
Federico Grillini ◽  
Jean-Baptiste Thomas ◽  
Sony George

The radiation captured in spectral imaging depends on both the complex light–matter interaction and the integration of the radiant light by the imaging system. In order to obtain material-specific information, it is important to define and invert an imaging process that takes into account both aspects. In this article, we investigate the use of several mixing models and evaluate their performances in the study of oil paintings. We propose an evaluation protocol, based on different features, i.e., spectral reconstruction, pigment mapping, and concentration estimation, which allows investigating the different properties of those mixing models in the context of spectral imaging. We conduct our experiment on oil-painted mockup samples of mixtures and show that models based on subtractive mixing perform the best for those materials.

2021 ◽  
Vol 11 (12) ◽  
pp. 5628
Author(s):  
Run Fang ◽  
Libo Zeng ◽  
Fan Yi

Multi-spectral imaging technique plays an important role in real-world applications such as medicine and medical detections. This paper proposes a cervical cancer cell screening method to simultaneously adopt TBS classification and DNA quantitative analysis for a single cell smear. Through using compound staining on a smear, the cytoplasm is stained by Papanicolauo and the nucleus is stained by Feulgen. The main evaluation parameter is the DNA content of the nucleus, not the subjective description of cell morphology, which is more objective than the TBS classification method and reduces the chances of missing a diagnosis due to subjective factors. Each nucleus has its own DI value and color image of the whole cell, which is convenient for doctors as it allows them to review and confirm the morphology of cells with a nucleus DI of over 2.5. Mouse liver smears and cervical cases are utilized as the measuring specimens to evaluate the performance of the microscope multi-spectral imaging system; illustrative results demonstrate that the proposed system qualifies, with high accuracy and reliability, and further presents wide application prospects in the early diagnosis of cervical cancer.


2021 ◽  
Author(s):  
◽  
J. N. Mendoza Chavarría

Spectral unmixing has proven to be a great tool for the analysis of hyperspectral data, with linear mixing models (LMMs) being the most used in the literature. Nevertheless, due to the limitations of the LMMs to accurately describe the multiple light scattering effects in multi and hyperspectral imaging, new mixing models have emerged to describe nonlinear interactions. In this paper, we propose a new nonlinear unmixing algorithm based on a multilinear mixture model called Non-linear Extended Blind Endmember and Abundance Extraction (NEBEAE), which is based on a linear unmixing method established in the literature. The results of this study show that proposed method decreases the estimation errors of the spectral signatures and abundance maps, as well as the execution time with respect the state of the art methods.


2007 ◽  
Vol 24 (12) ◽  
pp. B25 ◽  
Author(s):  
Mark A. Neifeld ◽  
Amit Ashok ◽  
Pawan K. Baheti

2011 ◽  
Vol 78 (11) ◽  
pp. 503-507 ◽  
Author(s):  
Martin De Biasio ◽  
T. Arnold ◽  
R. Leitner

2015 ◽  
Vol 41 (6) ◽  
pp. 585-595 ◽  
Author(s):  
Jinxing Liang ◽  
Xiaoxia Wan ◽  
Qiang Liu ◽  
Chan Li ◽  
Junfeng Li

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Isaac August ◽  
Yaniv Oiknine ◽  
Marwan AbuLeil ◽  
Ibrahim Abdulhalim ◽  
Adrian Stern

2021 ◽  
Author(s):  
Eleni Aloupogianni ◽  
Masahiro Ishikawa ◽  
Takaya Ichimura ◽  
Atsushi Sasaki ◽  
Naoki Kobayashi ◽  
...  

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