0000000000206851
AUTHOR
Matti A. Eskelinen
Miniature MOEMS hyperspectral imager with versatile analysis tools
The Fabry-Perot interferometers (FPI) are essential components of many hyperspectral imagers (HSI). While the Piezo-FPI (PFPI) are still very relevant in low volume, high performance applications, the tunable MOEMS FPI (MFPI) technology enables volume-scalable manufacturing, thus having potential to be a major game changer with the advantages of low costs and miniaturization. However, before a FPI can be utilized, it must be integrated with matching optical assembly, driving electronics and imaging sensor. Most importantly, the whole HSI system must be calibrated to account for wide variety of unwanted physical and environmental effects, that significantly influence quality of hyperspectral…
Multilabel segmentation of cancer cell culture on vascular structures with deep neural networks
New increasingly complex in vitro cancer cell models are being developed. These new models seem to represent the cell behavior in vivo more accurately and have better physiological relevance than prior models. An efficient testing method for selecting the most optimal drug treatment does not exist to date. One proposed solution to the problem involves isolation of cancer cells from the patients' cancer tissue, after which they are exposed to potential drugs alone or in combinations to find the most optimal medication. To achieve this goal, methods that can efficiently quantify and analyze changes in tested cell are needed. Our study aimed to detect and segment cells and structures from canc…
Remote Sensing of 3-D Geometry and Surface Moisture of a Peat Production Area Using Hyperspectral Frame Cameras in Visible to Short-Wave Infrared Spectral Ranges Onboard a Small Unmanned Airborne Vehicle (UAV)
Miniaturized hyperspectral imaging sensors are becoming available to small unmanned airborne vehicle (UAV) platforms. Imaging concepts based on frame format offer an attractive alternative to conventional hyperspectral pushbroom scanners because they enable enhanced processing and interpretation potential by allowing for acquisition of the 3-D geometry of the object and multiple object views together with the hyperspectral reflectance signatures. The objective of this investigation was to study the performance of novel visible and near-infrared (VNIR) and short-wave infrared (SWIR) hyperspectral frame cameras based on a tunable Fabry–Pérot interferometer (FPI) in measuring a 3-D digital sur…
SOFTWARE FRAMEWORK FOR HYPERSPECTRAL DATA EXPLORATION AND PROCESSING IN MATLAB
Abstract. This paper presents a user introduction and a general overview of the MATLAB software package hsicube developed by the author for simplifying the data manipulation and visualization tasks often encountered in hyperspectral analysis work, and the design principles and software development methods used by the author. The framework implements methods for slicing, masking, visualization and application of existing functions to hyperspectral data cubes without the need to use explicit indexing or reshaping, as well as enabling expressive syntax for combining these operations on the command line for highly efficient data analysis workflows. It also includes utilities for interfacing wit…
Hyperspectral imager calibration using ceramic color tiles (Conference Presentation)
Sets of chromatic and neutral ceramic tiles are widely used as measurement standards for reflectance factors in color applications. The usual instrument for color measurements is a spectrophotometer that measures the tiles using either a 0:45 or 45:0 illumination and viewing geometry, or with an integrating sphere in order to measure the reflectance factor in either specular excluded or specular included conditions. Having the corresponding measurements of the tile set from a calibrated instrument, systematic errors in the instrument under study can be diagnosed and corrected using a model of the errors and fitting it to the difference in measurements. One such is the Berns-Petersen model, …
Rapid Quantification of Microalgae Growth with Hyperspectral Camera and Vegetation Indices
Spectral cameras are traditionally used in remote sensing of microalgae, but increasingly also in laboratory-scale applications, to study and monitor algae biomass in cultures. Practical and cost-efficient protocols for collecting and analyzing hyperspectral data are currently needed. The purpose of this study was to test a commercial, easy-to-use hyperspectral camera to monitor the growth of different algae strains in liquid samples. Indices calculated from wavebands from transmission imaging were compared against algae abundance and wet biomass obtained from an electronic cell counter, chlorophyll a concentration, and chlorophyll fluorescence. A ratio of selected wavebands containing near…
CLUSTERING INCOMPLETE SPECTRAL DATA WITH ROBUST METHODS
Abstract. Missing value imputation is a common approach for preprocessing incomplete data sets. In case of data clustering, imputation methods may cause unexpected bias because they may change the underlying structure of the data. In order to avoid prior imputation of missing values the computational operations must be projected on the available data values. In this paper, we apply a robust nan-K-spatmed algorithm to the clustering problem on hyperspectral image data. Robust statistics, such as multivariate medians, are more insensitive to outliers than classical statistics relying on the Gaussian assumptions. They are, however, computationally more intractable due to the lack of closed-for…
PRACTICAL APPROACH FOR HYPERSPECTRAL IMAGE PROCESSING IN PYTHON
Abstract. Python is a very popular programming language among data scientists around the world. Python can also be used in hyperspectral data analysis. There are some toolboxes designed for spectral imaging, such as Spectral Python and HyperSpy, but there is a need for analysis pipeline, which is easy to use and agile for different solutions. We propose a Python pipeline which is built on packages xarray, Holoviews and scikit-learn. We have developed some of own tools, MaskAccessor, VisualisorAccessor and a spectral index library. They also fulfill our goal of easy and agile data processing. In this paper we will present our processing pipeline and demonstrate it in practice.