A Raman spectrometer 1 comprising a laser 1001 for illuminating a sample S under investigation, an auto-focusing system for focusing the laser 1001 on the sample S under investigation, and a detector 1010 for detecting Raman spectra emitted in response to illumination by the laser 1001. The auto-focusing system further comprises at least one adjustable focusing element for adjusting the location of the focus of the laser, a determination unit 1012 for determining a selected location for the focus of the laser 1001, and a control unit for adjusting the adjustable focusing element to focus the laser at said selected location determined by the determination unit 1012. The auto-focusing system is arranged under the control of software to enable determination of the selected location for the focus of the laser 1001.

There is provided a learning method. The method includes performing preprocessing on light emission data in a chamber of a plasma processing apparatus, setting a constraint for generating a regression equation representing a relationship between an etching rate of the plasma processing apparatus and the light emission data, selecting a learning target wavelength from the light emission data subjected to the preprocessing, and receiving selection of other sensor data different from the light emission data. The method further includes generating a regression equation based on the set constraint while using, as learning data, the selected wavelength, the received other sensor data, and the etching rate, and outputting the generated regression equation.

A non-contact system for the sensing the concentration of a compound includes a hyperspectral imaging device configured to capture a hyperspectral image of a fluid, a flow cell configured to enable the capturing of a hyperspectral image of a fluid, a process, and a memory. The memory includes instructions stored thereon which, when executed by the processor, cause the system to generate a hyperspectral image of the fluid in the flow cell, generate several spectral signals based on the hyperspectral image, provide the spectral signal as an input to a machine learning network, and predict by the machine learning network the concentration of a compound in a fluid.

A small, handheld Raman spectrometer device can be built from a laser, lenses, and a diffraction grating configured in a right-angle Raman spectroscopy geometry, and used in conjunction with a cell-phone camera to record the Raman spectra. The cell-phone-based Raman spectrometer system is suited to performing in-situ measurements of chemical and biological molecules.

A measurement method includes: (a) measuring an emission intensity for each wavelength of light detected from a plasma generated in a plasma processing apparatus at each different exposure time by a light receiving element; (b) specifying, with respect to each of a plurality of different individual wavelength ranges that constitutes a predetermined wavelength range, a distribution of the emission intensity in the individual wavelength range measured at an exposure time at which an emission intensity of a predetermined wavelength included in the individual wavelength range becomes an emission intensity within a predetermined range; (c) selecting a distribution of the emission intensity in the individual wavelength range from the distribution of the emission intensity specified in (b); and (d) outputting the distribution of the emission intensity selected for each individual wavelength range.

Systems and methods here may be used for automated capturing and analyzing spectrometer data of multiple sample gemstones on a stage, including mapping digital camera image data of samples, applying a Raman Probe to a first sample gemstone under evaluation on the stage, receiving spectrometer data of the sample gemstone from the probe, automatically moving the stage to a second sample, using the image data, and analyzing the other samples.

A system includes a first spectral modulator, a second spectral modulator, a light guide optically, a photodetector, and an electronic control device. The first spectral modulator receives sample light, and modulates the sample light according to a first spectral response pattern to produce first modulated light. The second spectral modulator receives the first modulated light from the first spectral modulator via the light guide, modulates the first modulated light according to a second spectral response pattern to produce second modulated light, and transmits the second modulated light to the photodetector. The photodetector measures an intensity of the second modulated light incident on the photodetector, and generates one or more signals corresponding to the intensity of the second modulated light. The electronic control device determines a spectral distribution of the sample light based on the one or more signals.

Systems and methods here may be used for automated capturing and analyzing spectrometer data of multiple sample gemstones on a stage, including mapping digital camera image data of samples, applying a Raman Probe to a first sample gemstone under evaluation on the stage, receiving spectrometer data of the sample gemstone from the probe, automatically moving the stage to a second sample, using the image data, and analyzing the other samples.

A signal processing method is performed by a computer. The signal processing method includes: obtaining first compressed image data including hyperspectral information and indicating a two-dimensional image in which the hyperspectral information is compressed, the hyperspectral information being luminance information on each of at least four wavelength bands included in a target wavelength range; extracting partial image data from the first compressed image data; and generating first two-dimensional image data corresponding to a first wavelength band and second two-dimensional image data corresponding to a second wavelength band from the partial image data.

A method begins by generating a received light spectrum at time T1 for a scene using a spectral imager that includes a plurality of spectral sensors, where a spectral sensor includes a spectral filter overlaying one or more first optical sensors and the sensing range for the plurality of spectral sensors together include a spectrum of wavelength and outputting information representative of a spectral image for the scene at T1 to a processing module. The method continues by using an image sensor to image the scene at time T2, where the image sensor includes a plurality of second optical sensors, and outputting information representative of an image of the scene at T2 to the processing module where the image of the scene has a spatial resolution that is higher than the spatial resolution of the spectral image. The method continues by producing a combined spectral image based on the information representative of a spectral image for the scene at T1 and the information representative of the image at T2 and correcting, based on the combined spectral image, an illuminant for one or more spatial areas of the scene to produce a corrected spectral image.