In recent years, Maritime Domain Awareness (MDA) has become important for national defense in Japan. Target detection using hyperspectral data is useful for MDA. In this study, we found that Correlation Matched Filter (CMF) has a better detection accuracy than Spectral Matched Filter (SMF), both of which are derived from Reed-Xiaoli Detector. CMF doesn't need to calculate the average value of the background spectrum, which is also advantageous in real-time processing. In addition, we could also show that it is possible to improve the detection accuracy by band selection in CMF. This increases the detection accuracy of foreign matter on the ocean.
Morphological patterns of tissues are important index for pathologists to tell the difference between cancer and non-cancer cells. However, diagnoses with human eyes and experience have limitations. For example, ovarian cancers are categorized into 4 types in the morphological forms. This classification does not thoroughly correspond to the malignancy. Even worse, there are cases that medicines are not effective when patients have the same type of ovarian cancer. That is why, the new method to diagnose the cancer cells are demanded. In this paper, we measured and analyzed the hyperspectral data of colon cancer nuclei and ovarian cancer nuclei and proved that hyperspectral camera has potential to distinguish the cancer in the early stage and to find the novel classification which corresponds to the cancer malignancy. Machine learning methods enabled us to distinguish four stages of colon canceration with 98.9% accuracy. In addition, two groups of ovarian cancer specimens created based on the hyperspectral data showed a significant difference on their cumulative survival curves.
Target detection using hyperspectral images is useful for Maritime Domain Awareness (MDA). For future application to MDA, in the previous study, targets on the sea was photographed with a hyperspectral camera mounted on a helicopter to demonstrate a target detection using a Reed-Xiaoli detector (RXD). Although the demonstration turned out to be successful, for there were many erroneous detections due to white waves, improvement of the detection accuracy was desired. In this study, pixels classified as white waves by random forest, which is a supervised machine learning method, were removed from pixels which were regarded as anomaly by RXD.As a result, 76% white waves were successfully removed. This study show that white wave removal is possible by machine learning. This will improve the detection accuracy of foreign matter on the ocean.
Hyperspectral Images are now used in the field of agriculture, cosmetics, and space exploring. Behind this fact, there is a result of efforts to contrive miniaturization and decrease in costs. This paper describes low-cost and small Hyperspectral Camera (HSC) under development and a method of utilizing it. Real Time Detection System for MDA is that government agencies put those cameras in small satellites and use them for MDA (Maritime Domain Awareness). We assume early detection of unidentified floating objects to find out disguised fishing ships and submarines.
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