DOI: 10.5281/zenodo.17493261
title: Dataset for "LOROS: Laboratory Simulations of the Optical RadiOmeter composed of CHromatic Imagers (OROCHI) Experiment of the Martian Moons eXploration (MMX) Mission"

description: This is the final dataset for published version.

This dataset hosts the image and numerical data analysed and derived in the accompanying Stabbins & Kameda article for the special issue of Progress in Earth and Planetary Science on instrumentation and preparations for the JAXA Martian Moons eXploration (MMX) mission. The paper describes and validates the performance of the Laboratory OROCHI Simulator (LOROS).

OROCHI (Optical RadiOmeter composed of CHromatic Imagers) is a multispectral multi-view imaging system for the JAXA MMX spacecraft, that will image Phobos and Deimos across 8 visible and near-infrared spectral channels with unprecedented spatial resolution, recording data that in synergy with the other instruments of the MMX spacecraft and rover will constrain hypotheses on the origin of the Martian moons.

LOROS is a laboratory simulator of OROCHI, constructed from commercial off-the-shelf parts.

The dataset for the characterisation and validation of LOROS is composed of the following sub-sets:

A. Modulation Transfer FunctionB. System ResponseC. Expected Reflectance of Carbonaceous Chondrite & Dark SpectralonD. Radiometric CalibrationE. Dark Spectralon Validation



Dataset A: Modulation Transfer Function
This dataset includes the table of results of MTF measurements of the slant-edge target at 5 different random orientations in the range of ~7--10°:

- mtf_results_07122023.csv


and the region-of-interest images, for each orientation and each LOROS channel, used to perform the analysis via the MTF Mapper software:

- mtf_measurements_07122023


The directory tree of measurements, for the nth orientation, is illustrated below. Region-of-interest images are stored under img, and are averaged over 25 repeat images to minimise random noise, have had dark frames subtracted, and have been converted from 12-bit to 8-bit grayscale images for compatibility with the MTF Mapper software. Modulation Transfer Function (MTF) and Spatial Frequency Response (SFR) diagnostics generated by MTF Mapper are stored in the results directory.

 

mtf_measurements_07122023

├── mtf_knifeedge_low_07122023_*n*

│ ├── img

│ │ ├── 0_850_img_ave.tif

│ │ ├── 1_475_img_ave.tif

│ │ ├── ...

│ ├── results

│ │ ├── 0_850_img_ave_annotated.jpg

│ │ ├── 0_850_img_ave_edge_mtf_values.txt

│ │ ├── 0_850_img_ave_edge_sfr_values.txt

│ │ ├── 1_475_img_ave_annotated.jpg

│ │ ├── ...

├── mtf_knifeedge_low_07122023_*n+1*

│ ├── img

│ │ ├── ...

 

This data constitutes part of Table 1 and Figure 2 of the manuscript.



Dataset B: System Response of LOROS and OROCHI

This dataset collects the illuminant spectral power distributions, filter transmission profiles and quantum efficiency data for LOROS and OROCHI, and presents the combined normalised system spectral transmission for each. All data gives wavelengths in units of nanometers.

The data is organised by system:

B_system_response├── LOROS├── OROCHI└── README.md

For LOROS, the illuminant data (lamp_brightness.csv) is the normalised spectral power distribution of the Hayashi-Repic LA-150UE lamp, recorded at Rikkyo University with an Ocean Optics HR4 spectrometer from 195 -- 1129 nm at 0.27 nm  intervals. The transmission data (loros_transmission_data_15012024.csv) for each filter of LOROS was also recorded at Rikkyo University with the Ocean Optics HR4 spectrometer from 195 -- 1129 nm at 0.27 nm  intervals, illuminated with the Hayashi-Repic LA-150UE lamp. Data for the quantum efficiency (sony_imx249_qe_spectral.csv) of the SONY IMX249 CMOS sensor used in all 8 of the DMX 33GX249 cameras of LOROS was extracted from the DMX 33GX249 Technical Reference Manual (The Imaging Source). The complete system response (mmx_loros_system_response.csv) is the combination of these components, normalised to the peak value of each filter.

└── LOROS  ├── lamp_brightness.csv  ├── loros_transmission_data_15012024.csv  ├── sony_imx249_qe_spectral.csv  └── mmx_loros_system_response.csv

For OROCHI, the illuminant data (wehrli85.csv) is the normalised spectral power distribution of the Top-of-Atmosphere Solar Irradiance (Wehrli 85). The transmission data (orochi_transmission_synethsized.csv) for each filter of OROCHI was synethsized using a 15th-order super-Gaussian, with the central wavelengths and full-widths-at-half-maximum expected for OROCHI. Data for the quantum efficiency (kai_08051_qe_spectral.csv) of the KAI-08051 CCD sensor used in all 8 of the cameras of OROCHI was extracted from the KAI-08051 datasheet (OnSemi). The complete system response (mmx_orochi_system_response.csv) is the combination of these components, normalised to the peak value of each filter.

├── OROCHI  ├── wehrli85.csv  ├── orochi_transmission_synthesized.csv  ├── kai_08051_qe_spectral.csv  └── mmx_orochi_system_response.csv

This data constitutes figure 2 of the manuscript.

Dataset C: Expected Reflectance of Carbonaceous Chondrite & Dark Spectralon
This dataset includes the high-resolution ($\delta\lambda$=1 nm) reference reflectance spectra of the representative Carbonaceous Chondrite meteorite (Nogoya) and the 5% reflectance Spectralon calibration target (SCT5):

- highres_input.csv


and the resampled spectra of these materials expected for OROCHI and LOROS filter wavelengths:


- loros_observation.csv

- orochi_observation.csv


C_expected_reflectance

├── README.md

├── highres_input.csv

├── loros_observation.csv

└── orochi_observation.csv


This data constitutes Table 1 and Figure 11 of the manuscript.

 





Dataset D: Radiometric Calibration
This dataset contains the image and derived data for 4 experiments with different illumination conditions for characterising the radiometric response of each of the 8 channels of LOROS.



This dataset contributes to Tables 2 - 4 and Figures 4 - 10 of the manuscript.


The final derived metrics are hosted in the spreadsheet:


- measured_sensor_properties.csv


and image data and intermediary derived properties for each experiment are stored in the


- experiments


directory.


D_radiometric_calibration

├── README.md

├── experiments

│ ├── F*S5L10

│ ├── F*S99L10

│ ├── FGS99L2

│ └── FGS99L10

└── measured_sensor_properties.csv


experiments Directories
In the directory of each experiment are sub-directories hosting Photon Transfer and Dark Transfer datasets, and a spreadsheet of derived metrics of these.

 

D_radiometric_calibration

├── README.md

├── experiments

│ ├── F*S5L10

│ │ ├── dark_transfer_curve

│ │ ├── photo_transfer_curve

│ │ └── F*S5L10_derived_properties.csv

│ └── ...

└── measured_sensor_properties.csv

 


 

Derived Properties

 

The spreadsheet ([experiment]_derived_properties.csv) collecting the properties derived from each experiment holds the following information, that has been extracted from the Photon Transfer and Dark Transfer curves as described in §4.2 of the manuscript:


camera # The camera number and wavelength

k_adc # Sensitivity (e-/DN)

full_well_e # Saturation Capacity (electrons)

full_well_dn # Saturation Capacity (Digital Numbers)

read_noise_e # Read Noise (electrons)

read_noise_dn # Read Noise (Digital Numbers)

bias_e # Offset (electrons)

bias_dn # Offset (Digital Numbers)

dark_current_e # Dark Current (electrons/second)

dark_current_dn # Dark Current (Digital Numbers/second)

DR # Dynamic Range

lin_min # Minimum Linearity Error

lin_max # Maximum Linearity Error

linearity # Average Linearity Error

snr_max # Maximum Signal-to-Noise Ratio

t_exp_min # Minimum Exposure used in experiment (seconds)

t_exp_max # Maximum Exposure used in experiment (seconds)

expected_response # Expected Response (or 'Digital Flux') for OROCHI^12 at Phobos (Digital Numbers/second)

response # Fitted Response (or 'Digital Flux') (Digital Numbers/second)


These values are given for each channel of LOROS, as well as the expected values for LOROS in off-the-shelf configuration (with no gain adjustment), LOROS with the gain adjustment, and OROCHI if downsampled to 12-bit resolution digital numbers.


This data constitutes Table 2 of the manuscript.


Dark Transfer Curve


The dark_transfer_curve directory hosts the derived Dark Transfer Curve data (derived_data) and the source region-of-interest dark image pair data (raw_data) for each LOROS channel.


dark_transfer_curve

├── derived_data

│ ├── F*S5L10_0_850_dtc.csv

│ ├── F*S5L10_1_475_dtc.csv

│ ├── F*S5L10_2_400_dtc.csv

│ ├── F*S5L10_3_550_dtc.csv

│ ├── F*S5L10_4_725_dtc.csv

│ ├── F*S5L10_5_950_dtc.csv

│ ├── F*S5L10_6_650_dtc.csv

│ └── F*S5L10_7_550_dtc.csv

└── raw_data

├── 0_850

│ ├── 850_10095570us_1_calibration.tif

│ ├── 850_10095570us_2_calibration.tif

│ ├── 850_104us_1_calibration.tif

│ ├── 850_104us_2_calibration.tif

│ ├── ...

├── 1_475

├── 2_400

├── 3_550

├── 4_725

├── 5_950

├── 6_650

├── 7_550

└── camera_config.csv


The raw_data directory hosts a dark image pair for each exposure time used, and the camera_config.csv spreadsheet gives metadata for the system configuration, including the coordinates and dimensions of the region-of-interest for each channel.


The dark transfer curve for each experiment and each channel ([experiment]_[channel]_[wavelength]_dtc) gives the data derived from each raw image data, with the following values:


exposure # exposure duration (seconds)

n_pix # number of pixels in the region of interest

mean # average value of the region of interest

std_t # total standard deviation of the region of interest

std_rs # read+shot-noise standard deviation, copmuted from the difference of the image pair


This data constitutes Figures 6 and 9 of the manuscript.


Photon Transfer


The photon_transfer_curve directory hosts the derived Photon Transfer Curve data (derived_data) and the source region-of-interest illuminated image pairs and associated dark frame image data (raw_data) for each LOROS channel.


photo_transfer_curve

├── derived_data

│ ├── F*S5L10_0_850_ptc.csv

│ ├── F*S5L10_1_475_ptc.csv

│ ├── F*S5L10_2_400_ptc.csv

│ ├── F*S5L10_3_550_ptc.csv

│ ├── F*S5L10_4_725_ptc.csv

│ ├── F*S5L10_5_950_ptc.csv

│ ├── F*S5L10_6_650_ptc.csv

│ └── F*S5L10_7_550_ptc.csv

└── raw_data

├── 0_850

│ ├── 850_104us_1_calibration.tif

│ ├── 850_104us_2_calibration.tif

│ ├── 850_104us_d_drk.tif

│ ├── 850_105828us_1_calibration.tif

│ ├── ...

├── 1_475

├── 2_400

├── 3_550

├── 4_725

├── 5_950

├── 6_650

├── 7_550

└── camera_config.csv


The raw_data directory hosts an image pair and dark frame for each exposure time used, and the camera_config.csv spreadsheet gives metadata for the system configuration, including the coordinates and dimensions of the region-of-interest for each channel.


The photon transfer curve for each experiment and each channel ([experiment]_[channel]_[wavelength]_ptc) gives the data derived from each raw image data, with the following values across the region-of-interest:


exposure # exposure duration (seconds)

n_pix # number of pixels in the region of interest

mean # average value (Digital Numbers)

std_t # total standard deviation (Digital Numbers)

std_rs # read+shot-noise standard deviation (Digital Numbers), computed from the difference of the image pair

d_mean # average value of the dark (Digital Numbers)

d_dsnu # Dark Signal Nonuniformity (Digital Numbers)

std_s # Shot Noise (read noise removed) (Digital Numbers)

k_adc # Sensitivity (note this the point-wise sensitivity, rather than fitted) (electrons/Digital Number)

linearity # Linearity Error (point-wise distance to least-squares linear fit) (%)

snr # Signal-to-Noise Ratio, derived from shot-noise (point-wise)

snr_t # Signal-to-Noise Ratio, derived from total noise (point-wise)

e- # Electron count, derived from sensitivity

e-_noise # Electron shot-noise, derived from sensitivity


This data constitutes Figures 4, 5, 7, 8 & 10 of the manuscript.


Measured Sensor Properties


The measured_sensor_properties.csv spreadsheet collects and averages the following metrics over the 4 experiments performed, to give the values for each channel, along with the expected values for LOROS in off-the-shelf configuration, gain-adjusted LOROS, and OROCHI downsampled to 12-bit resolution.


Read Noise (DN)Read Noise (e-)Saturation Capacity (DN)Saturation Capacity (e-)Full-Well (e-)Sensitivity (e-/DN)Linearity Error (%)Dark Signal@30°C (DN/s)Dark Signal@30°C (e-/s)SNR MaxDynamic Range (bits)Bias (DN)PRNU1288 (%)DSNU1288 (DN)


This data constitutes Table 3 of the manuscript.

 



Dataset E: Dark Spectralon Validation
This dataset contains the raw image and derived data used to demonstrate the ability of LOROS to measure the spectral reflectance of the 5% reflectance Spectralon calibration target (SCT5).

The image data is hosted in the directory:


- raw_data


and the processed data (e.g. reflectance products) are hosted in the directory:


- processed_data


E_dark_spectralon_validation

├── processed_data

│ ├── SCT5

│ └── SCT99

├── raw_data

│ ├── SCT5

│ ├── SCT5_dark

│ ├── SCT99

│ └── SCT99_dark

└── README.md


Raw Data


The raw data directory contains images captured of SCT5 and SCT99 (99% reflectance white Spectralon), and accompanying dark frames, hosted in the SCT5_dark and SCT99_dark frames respectively.


For each channel, 25 repeat images have been captured for the illuminated and dark frames.


Processed Data


The processed SCT99 and SCT5 datasets differ slightly. Both include:


├── img

├── rfl

└── rois


directories, with the SCT99 scene also including a cal directory.


img hosts a set of context figures, showing the regions of interest selected, fits hosts the floating point mean (ave), standard error (err), standard deviation (std) and single-frame (one), all in units of Digital Number, after dark frame subtraction, flat-fielding and linearity correction. uint8 hosts the same data rescaled to 8-bit resolution, for quick-view.


rfl hosts the same set as img, after conversion to units of reflectance against the results of the SCT99 calibration (see §3.5 of the manuscript).


rois gives plots of the mean and error of the reflectance spectrum of the region of interest, as well as the Signal-to-Noise Ratio, as well as the data for each region-of-interest (roi_data).


cal also gives context figures for each channel region-of-interest, as converted to units of reflectance coefficients (1/DN/s).