8 releases
0.3.1 | Mar 30, 2022 |
---|---|
0.3.0 | Mar 22, 2022 |
0.2.4 | Feb 18, 2022 |
0.2.1 | Nov 3, 2021 |
0.1.4 | May 25, 2021 |
#374 in Images
5MB
7K
SLoC
Mars Raw Image Utilities
A set of utilities for processing and calibration of imagery from either the Curiosity or Perseverance rovers. Meant to be used on publicly available images.
Implemented calibration steps include (varying per instrument):
Mission | Camera | Decompand | Debayer | Inpaint | Flats | HPC* |
---|---|---|---|---|---|---|
MSL | MastCam | ☑ | ☑ | |||
MSL | MAHLI | ☑ | ☑ | ☑ | ☑ | |
MSL | NavCam | ☑ | ☑ | ☑ | ||
MSL | Rear Haz | ☑ | ☑ | ☑ | ||
MSL | Front Haz | ☑ | ☑ | ☑ | ||
MSL | ChemCam RMI | ☑ | ||||
Mars2020 | Mastcam-Z | ☑ | ☑ | ☑ | ||
Mars2020 | NavCam | ☑ | ||||
Mars2020 | Rear Haz | ☑ | ||||
Mars2020 | Front Haz | ☑ | ||||
Mars2020 | Watson | ☑ | ☑ | ☑ | ||
Mars2020 | SuperCam | ☑ | ☑ | |||
Ingenuity | Nav | ☑ | ||||
Ingenuity | Color | ☑ | ||||
InSight | IDC | ☑ | ☑ | |||
InSight | ICC | ☑ | ☑ |
* Hot pixel detection and correction
Additional instruments will be implemented more or less whenever I get to them...
Building from source:
A working Rust (https://www.rust-lang.org/) installation is required for building.
So far I've only tested building on Ubuntu 21.10, natively and within the Windows Subsystem for Linux on Windows 10, and on MacOSX Catalina. Within the project folder, the software can be built for testing via cargo build
and individual binaries can be run in debug mode via, for example, cargo run --bin m20_fetch_raw -- -i
To build successfully on Linux, you'll likely need the following packages installed via apt:
- libssl-dev (Ubuntu)
- openssl-devel (RHEL, CentOS, Fedora)
Clone from git:
git clone git@github.com:kmgill/mars-raw-utils.git
cd mars-raw-utils/
git submodule init
git submodule update
Install via cargo:
This is the easiest installation method for *nix-based systems. It has not been tested in Windows.
cargo install --path .
mkdir ~/.marsdata
cp mars-raw-utils-data/caldata/* ~/.marsdata
NOTE: You can set $MARS_RAW_DATA in ~/.bash_profile if a custom data directory is required.
Install via apt (Debian, Ubuntu, ...):
cargo install cargo-deb
cargo deb
sudo apt install ./target/debian/mars_raw_utils_0.1.3_amd64.deb
NOTE: Adjust the output debian package filename to what is outputted by build.
Install via rpm (RHEL, CentOS, Fedora, ...)
cargo install cargo-rpm
cp -v mars-raw-utils-data/caldata/* .rpm/
cargo rpm build -v
rpm -ivh target/release/rpmbuild/RPMS/x86_64/mars_raw_utils-0.1.3-1.el8.x86_64.rpm
NOTE: Adjust the output rpm package filename to what is created by build.
Docker:
The dockerfile demonstrates a method for building an installable debian package, or you can use the container itself:
docker build -t mars_raw_utils .
docker run --name mars_raw_utils -dit mars_raw_utils
docker exec -it mars_raw_utils bash
Builds for MacOSX (maybe via Homebrew?) and Windows are in the plan. Though the project has built and run from MacOSX and Windows, I haven't worked out the installation method in a way that handles the calibration data.
Building RPMs using Docker
CentOS targetted RPMs can be built using dockerbuild.sh
which will result in the build artifacts being placed into the target
directory.
Specifying Calibration Data Location:
By default, if the software is installed using the .deb file in Debian/Ubuntu, the calibration files will be located in /usr/share/mars_raw_utils/data/
. In Homebrew on MacOS, they will be located in /usr/local/share/mars_raw_utils/data/
. For installations using cargo install --path .
or custom installations, you can use the default ~/.marsdata
or set the calibration file directory by using the MARS_RAW_DATA
environment variable. The variable will override the default locations (if installed via apt or rpm), as well.
Calibration Profiles
Calibration files are used to specify commonly used parameters for the various instruments and output product types. The files are in toml format and if not specified by their absolute path, need to be discoverable in a known calibration folder.
An example profile
apply_ilt = true
red_scalar = 1.16
green_scalar = 1.0
blue_scalar = 1.05
color_noise_reduction = false
color_noise_reduction_amount = 0
hot_pixel_detection_threshold = 0
filename_suffix = "rjcal-rad"
Mars Science Laboratory (Curiosity):
Fetch Raws:
USAGE:
msl_fetch_raw [FLAGS] [OPTIONS]
FLAGS:
-h, --help Prints help information
-l, --list Don't download, only list results
-t, --thumbnails Download thumbnails in the results
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-c, --camera <camera>... M20 Camera Instrument(s)
-M, --maxsol <maxsol> Ending Mission Sol
-m, --minsol <minsol> Starting Mission Sol
-n, --num <num> Max number of results
-p, --page <page> Results page (starts at 1)
-S, --seqid <seqid> Specific sequence id or substring
-s, --sol <sol> Mission Sol
Examples:
Show available instruments:
msl_fetch_raw -i
List what's available for Mastcam on sol 3113: (remove the -l
to download the images)
msl_fetch_raw -c MASTCAM -s 3113 -l
List what's available for NAV_RIGHT between sols 3110 and 3112: (remove the -l
to download the images)
msl_fetch_raw -c NAV_RIGHT -m 3110 -M 3112 -l
Download NAV_RIGHT during sols 3110 through 3112, filtering for sequence id NCAM00595:
msl_fetch_raw -c NAV_RIGHT -m 3110 -M 3112 -S NCAM00595
MAHLI Calibration:
USAGE:
msl_mahli_calibrate [FLAGS] [OPTIONS] --inputs <INPUT>...
FLAGS:
-h, --help Prints help information
-n Only new images. Skipped processed images.
-r, --raw Raw color, skip ILT
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-B, --blue <BLUE> Blue weight
-G, --green <GREEN> Green weight
-i, --inputs <INPUT>... Input
-P, --profile <PARAM_CAL_PROFILE> Calibration profile file path
-R, --red <RED> Red weight
Common Color Correction Multiples:
- RED: 1.16
- GREEN: 1.00
- BLUE: 1.05
Common Color Correction Multiples (White Balanced):
- RED: 0.8
- GREEN: 1.0
- BLUE: 1.543
Examples:
Calibrate a directory of JPEGs, applying color correction values:
msl_mahli_calibrate -i *jpg -v -R 1.16 -G 1.00 -B 1.05
MastCam:
USAGE:
msl_mcam_calibrate [FLAGS] [OPTIONS] --inputs <INPUT>...
FLAGS:
-h, --help Prints help information
-n Only new images. Skipped processed images.
-r, --raw Raw color, skip ILT
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-B, --blue <BLUE> Blue weight
-c, --color_noise_reduction <COLOR_NOISE_REDUCTION> Color noise reduction amount in pixels
-G, --green <GREEN> Green weight
-i, --inputs <INPUT>... Input
-P, --profile <PARAM_CAL_PROFILE> Calibration profile file path
-R, --red <RED> Red weight
Recommended Color Correction Multiples:
- RED: 0.965
- GREEN: 0.985
- BLUE: 1.155
Examples:
Calibrate a directory of JPEGs, applying color correction values:
msl_mcam_calibrate -i *jpg -v -R 0.965 -G 0.985 -B 1.155
Calibrate a directory of JPEGs, skipping ILT conversion (decompanding):
msl_mcam_calibrate -i *jpg -v -r
Calibrate a directory of JPEGs, applying color noise reduction with a chroma blur radius of 21 pixels:
msl_mcam_calibrate -i *jpg -v -c 21
Engineering Cameras (Navcam, FHAZ, RHAZ):
USAGE:
msl_ecam_calibrate [FLAGS] [OPTIONS] --inputs <INPUT>...
FLAGS:
-h, --help Prints help information
-n Only new images. Skipped processed images.
-r, --raw Raw color, skip ILT (not currently used)
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-B, --blue <BLUE> Blue weight
-G, --green <GREEN> Green weight
-t, --hpc_threshold <THRESHOLD> Hot pixel correction variance threshold
-i, --inputs <INPUT>... Input
-P, --profile <PARAM_CAL_PROFILE> Calibration profile file path
-R, --red <RED> Red weight
Examples:
Calibrate a directory of JPEGs:
msl_ecam_calibrate -i *jpg -v
Calibrate a directory of JPEGs, apply a hot pixel detection with a threshold of 2.5 standard deviations:
msl_ecam_calibrate -i *jpg -v -t 2.5
ChemCam RMI:
USAGE:
msl_ccam_calibrate [FLAGS] --inputs <INPUT>...
FLAGS:
-h, --help Prints help information
-n Only new images. Skipped processed images.
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-i, --inputs <INPUT>... Input
Mars 2020 (Perseverance):
Fetch Raws:
USAGE:
m20_fetch_raw [FLAGS] [OPTIONS]
FLAGS:
-h, --help Prints help information
-l, --list Don't download, only list results
-t, --thumbnails Download thumbnails in the results
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-c, --camera <camera>... M20 Camera Instrument(s)
-M, --maxsol <maxsol> Ending Mission Sol
-m, --minsol <minsol> Starting Mission Sol
-n, --num <num> Max number of results
-p, --page <page> Results page (starts at 1)
-S, --seqid <seqid> Specific sequence id or substring
-s, --sol <sol> Mission Sol
MastCam-Z:
USAGE:
m20_zcam_calibrate [FLAGS] [OPTIONS] --inputs <INPUT>...
FLAGS:
-h, --help Prints help information
-n Only new images. Skipped processed images.
-r, --raw Raw color, skip ILT
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-B, --blue <BLUE> Blue weight
-G, --green <GREEN> Green weight
-i, --inputs <INPUT>... Input
-P, --profile <PARAM_CAL_PROFILE> Calibration profile file path
-R, --red <RED> Red weight
Watson:
USAGE:
m20_watson_calibrate [FLAGS] [OPTIONS] --inputs <INPUT>...
FLAGS:
-h, --help Prints help information
-n Only new images. Skipped processed images.
-r, --raw Raw color, skip ILT
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-B, --blue <BLUE> Blue weight
-G, --green <GREEN> Green weight
-i, --inputs <INPUT>... Input
-P, --profile <PARAM_CAL_PROFILE> Calibration profile file path
-R, --red <RED> Red weight
Engineering Cameras (Navcam, FHAZ, RHAZ):
SAGE:
m20_ecam_calibrate [FLAGS] [OPTIONS] --inputs <INPUT>...
FLAGS:
-h, --help Prints help information
-n Only new images. Skipped processed images.
-r, --raw Raw color, skip ILT
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-B, --blue <BLUE> Blue weight
-G, --green <GREEN> Green weight
-i, --inputs <INPUT>... Input
-P, --profile <PARAM_CAL_PROFILE> Calibration profile file path
-R, --red <RED> Red weight
SuperCam
USAGE:
m20_scam_calibrate [FLAGS] [OPTIONS] --inputs <INPUT>...
FLAGS:
-h, --help Prints help information
-n Only new images. Skipped processed images.
-r, --raw Raw color, skip ILT
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-B, --blue <BLUE> Blue weight
-G, --green <GREEN> Green weight
-i, --inputs <INPUT>... Input
-P, --profile <PARAM_CAL_PROFILE> Calibration profile file path
-R, --red <RED> Red weight
Ingenuity Nav Camera:
USAGE:
m20_hnav_calibrate [FLAGS] --inputs <INPUT>...
FLAGS:
-h, --help Prints help information
-n Only new images. Skipped processed images.
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-i, --inputs <INPUT>... Input
Ingenuity Color Camera (RTE):
USAGE:
m20_hrte_calibrate [FLAGS] [OPTIONS] --inputs <INPUT>...
FLAGS:
-h, --help Prints help information
-n Only new images. Skipped processed images.
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-B, --blue <BLUE> Blue weight
-G, --green <GREEN> Green weight
-i, --inputs <INPUT>... Input
-P, --profile <PARAM_CAL_PROFILE> Calibration profile file path
-R, --red <RED> Red weight
InSight
Fetch Raws:
...
Instrument Context Camera (ICC):
USAGE:
nsyt_icc_calibrate [FLAGS] [OPTIONS] --inputs <INPUT>...
FLAGS:
-h, --help Prints help information
-n Only new images. Skipped processed images.
-r, --raw Raw color, skip ILT
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-B, --blue <BLUE> Blue weight
-G, --green <GREEN> Green weight
-i, --inputs <INPUT>... Input
-P, --profile <PARAM_CAL_PROFILE> Calibration profile file path
-R, --red <RED> Red weight
Instrument Deployment Camera (IDC):
USAGE:
nsyt_idc_calibrate [FLAGS] [OPTIONS] --inputs <INPUT>...
FLAGS:
-h, --help Prints help information
-n Only new images. Skipped processed images.
-r, --raw Raw color, skip ILT
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-B, --blue <BLUE> Blue weight
-G, --green <GREEN> Green weight
-i, --inputs <INPUT>... Input
-P, --profile <PARAM_CAL_PROFILE> Calibration profile file path
-R, --red <RED> Red weight
Hot Pixel Correction Filter
Attempt at hot pixel detection and removal.
Method:
For each pixel (excluding image border pixels):
- Compute the standard deviation of a window of pixels (3x3, say)
- Compute the z-score for the target pixel
- If the z-score exceeds a threshold variance (example: 2.5) from the mean we replace the pixel value with a median filter
USAGE:
hpc_filter [FLAGS] [OPTIONS] --inputs <INPUT>...
FLAGS:
-h, --help Prints help information
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-t, --hpc_threshold <THRESHOLD> Hot pixel correction variance threshold
-w, --hpc_window <WINDOW_SIZE> Hot pixel correction window size
-i, --inputs <INPUT>... Input
Inpainting Filter
Applies a basic inpainting filter on a set of input images. Inpainting regions need to be marked in red (rgb 255, 0, 0).
USAGE:
inpaint_filter [FLAGS] --inputs <INPUT>...
FLAGS:
-h, --help Prints help information
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-i, --inputs <INPUT>... Input
Upscale Experiment (Deprecated)
An experiment in smooth image upscaling using the median-based inpainting algorithm.
USAGE:
upscale [FLAGS] --factor <FACTOR> --inputs <INPUT>...
FLAGS:
-h, --help Prints help information
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-f, --factor <FACTOR> Scale factor
-i, --inputs <INPUT>... Input
Crop
USAGE:
crop [FLAGS] --crop <WINDOW_SIZE> --inputs <INPUT>...
FLAGS:
-h, --help Prints help information
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-c, --crop <WINDOW_SIZE> Crop as x,y,width,height
-i, --inputs <INPUT>... Input
Debayer
Apply Malvar Demosaicking (Debayer) on a grayscale bayer-pattern image. Optionally apply a color noise reduction.
USAGE:
debayer [FLAGS] [OPTIONS] --inputs <INPUT>...
FLAGS:
-h, --help Prints help information
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-c, --color_noise_reduction <COLOR_NOISE_REDUCTION> Color noise reduction amount in pixels
-i, --inputs <INPUT>... Input
Levels
Apply levels adjustments to an image. Analogous to 'Levels' in Photoshop or GIMP.
USAGE:
levels [FLAGS] [OPTIONS] --inputs <INPUT>...
FLAGS:
-h, --help Prints help information
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-b, --blacklevel <BLACK_LEVEL> Black level
-g, --gamma <PARAM_GAMMA> Gamma
-i, --inputs <INPUT>... Input
-w, --whitelevel <WHITE_LEVEL> White level
Change Detection (Dust devils, clouds)
Calculates a per-frame differential from a mean across a series of images. Intended for use with MSL and Mars2020 dust devil movies and sky surveys. Optional options are for contrast enhancement through Photoshop-like black level, white level, and gamma.
USAGE:
diffgif [FLAGS] [OPTIONS] --inputs <INPUT>... --output <OUTPUT>
FLAGS:
-h, --help Prints help information
-v Show verbose output
-V, --version Prints version information
OPTIONS:
-b, --blacklevel <BLACK_LEVEL> Black level
-d, --delay <PARAM_DELAY> Interframe delay in increments of 10ms
-g, --gamma <PARAM_GAMMA> Gamma
-i, --inputs <INPUT>... Input
-l, --lowpass <PARAM_LOWPASS> Lowpass window size
-o, --output <OUTPUT> Output
-p, --prodtype <PARAM_PRODUCT_TYPE> Product type (std, diff, stacked)
-w, --whitelevel <WHITE_LEVEL> White level
Examples
Dust Devils, MSL Sol 3372, Seq id NCAM00595:
msl_fetch_raw -c NAV_RIGHT_B -s 3372 -S NCAM00595
msl_ecam_calibrate -i *JPG -v -t 2.0
diffgif -i *NCAM00595*-rjcal.png -o DustDevilMovie_Sol3372.gif -v -b 0 -w 2.0 -g 2.5 -l 5 -d 20
Cloud motion and shadows, MSL Sol 3325, Seq id NCAM00556:
msl_fetch_raw -c NAV_RIGHT -s 3325
msl_ecam_calibrate -i *JPG -v -t 2.0
diffgif -i *NCAM00556*-rjcal.png -o CloudShadow_3325.gif -v -b 0 -w 1.0 -g 2.5 -l 5 -d 20
Clouds, zenith movie, MSL Sol 3325, Seq id NCAM00551:
msl_fetch_raw -c NAV_RIGHT -s 3325
msl_ecam_calibrate -i *JPG -v -t 2.0
diffgif -i *NCAM00551*-rjcal.png -o CloudZenith_3325.gif -v -b 0 -w 3.0 -g 1.0 -l 5 -d 20
Data Update Checks
Fetches information as to the latest updated sols.
Example Output:
$ msl_latest
Latest data: 2022-02-23T18:30:03Z
Latest sol: 3395
Latest sols: [3365, 3374, 3376, 3378, 3390, 3393, 3394, 3395]
New Count: 364
Sol Count: 225
Total: 894201
$ m20_latest
Latest data: 2022-02-23T10:22:33Z
Latest sol: 359
Latest sols: [349]
New Count: 270
Sol Count: 99
Total: 217981
$ nsyt_latest
Latest data: 2022-02-14T15:11:15Z
Latest sol: 1144
Latest sols: [1144]
New Count: 2
Sol Count: 2
Total: 6353
Mission Dates
Mission time and sol are available for MSL, Mars2020, and InSight via msl_date
, m20_date
, and nsyt_date
, respectively.
Currently, the output provides valules for the Mars Sol Date, coordinated Mars time, mission sol, mission time (LMST), local true color time, and areocentric solar longitude. The algorithm used for the calculation is based on James Tauber's marsclock.com and is exposed via time::get_lmst()
.
Example Output:
$ msl_date
Mars Sol Date: 52391.26879394437
Coordinated Mars Time: 06:27:03.797
Mission Sol: 3122
Mission Time: 15:36:49.805 LMST
Local True Solar Time: 15:29:37.673 LTST
Solar Longitude: 47.04093399663567
$ m20_date
Mars Sol Date: 52391.270293050664
Coordinated Mars Time: 06:29:13.320
Mission Sol: 87
Mission Time: 11:38:56.520 LMST
Local True Solar Time: 11:31:44.417 LTST
Solar Longitude: 47.04161842268443
$ nsyt_date
Mars Sol Date: 52391.27048977531
Coordinated Mars Time: 06:29:30.317
Mission Sol: 880
Mission Time: 15:31:59.933 LMST
Local True Solar Time: 15:24:47.833 LTST
Solar Longitude: 47.041708238462114
References:
Bell, J. F. et al. (2017), The Mars Science Laboratory Curiosity rover Mastcam instruments: Preflight and in‐flight calibration, validation, and data archiving, Earth and Space Science, 4, 396– 452, doi:10.1002/2016EA000219. https://doi.org/10.1002/2016EA000219
Hayes, A.G., Corlies, P., Tate, C. et al. Pre-Flight Calibration of the Mars 2020 Rover Mastcam Zoom (Mastcam-Z) Multispectral, Stereoscopic Imager. Space Sci Rev 217, 29 (2021). https://doi.org/10.1007/s11214-021-00795-x
Edgett, K.S., Yingst, R.A., Ravine, M.A. et al. Curiosity’s Mars Hand Lens Imager (MAHLI) Investigation. Space Sci Rev 170, 259–317 (2012). https://doi.org/10.1007/s11214-012-9910-4
Edgett, K. S., M. A. Caplinger, J. N. Maki, M. A. Ravine, F. T. Ghaemi, S. McNair, K. E. Herkenhoff, B. M. Duston, R. G. Willson, R. A. Yingst, M. R. Kennedy, M. E. Minitti, A. J. Sengstacken, K. D. Supulver, L. J. Lipkaman, G. M. Krezoski, M. J. McBride, T. L. Jones, B. E. Nixon, J. K. Van Beek, D. J. Krysak, and R. L. Kirk (2015) Curiosity’s robotic arm-mounted Mars Hand Lens Imager (MAHLI): Characterization and calibration status, MSL MAHLI Technical Report 0001 (version 1: 19 June 2015; version 2: 05 October 2015). doi:10.13140/RG.2.1.3798.5447 https://doi.org/10.13140/RG.2.1.3798.5447
Bell, J. F. et al. (2017), The Mars Science Laboratory Curiosity rover Mastcam instruments: Preflight and in‐flight calibration, validation, and data archiving, Earth and Space Science, 4, 396– 452, doi:10.1002/2016EA000219. https://doi.org/10.1002/2016EA000219
Deen, R., Zamani, P., Abarca, H., Maki, J. InSight (NSYT) Software Interface Specification Camera Experiment Data Record (EDR) and Reduced Data Record (RDR) Data Products (version 3.3: 26 June 2019) https://pds-imaging.jpl.nasa.gov/data/nsyt/insight_cameras/document/insight_cameras_sis.pdf
Edgett, Kenneth & Caplinger, Michael & Ravine, Michael. (2019). Mars 2020 Perseverance SHERLOC WATSON Camera Pre-delivery Characterization and Calibration Report. 10.13140/RG.2.2.18447.00165. https://www.researchgate.net/publication/345959204_Mars_2020_Perseverance_SHERLOC_WATSON_Camera_Pre-delivery_Characterization_and_Calibration_Report
Maurice, Sylvestre & Wiens, R. & Mouélic, S. & Anderson, R. & Beyssac, O. & Bonal, L. & Clegg, S. & Deflores, L. & Dromart, G. & Fischer, W. & Forni, O. & Gasnault, O. & Grotzinger, J. & Johnson, Jordanlee & Martínez-Frías, Jesús & Mangold, N. & McLennan, S. & Montmessin, F. & Rull, Fernando & Sharma, Shiv. (2015). The SuperCam Instrument for the Mars2020 Rover. European Planetary Science Congress 2015. 10. https://www.researchgate.net/publication/283271532_The_SuperCam_Instrument_for_the_Mars2020_Rover
J. -M. Reess, Marion Bonafous, L. Lapauw, O. Humeau, T. Fouchet, P. Bernardi, Ph. Cais, M. Deleuze, O. Forni, S. Maurice, S. Robinson, R. C. Wiens, "The SuperCam infrared instrument on the NASA MARS2020 mission: performance and qualification results," Proc. SPIE 11180, International Conference on Space Optics — ICSO 2018, 1118037 (12 July 2019); https://doi.org/10.1117/12.2536034
Wiens, R.C., Maurice, S., Barraclough, B. et al. The ChemCam Instrument Suite on the Mars Science Laboratory (MSL) Rover: Body Unit and Combined System Tests. Space Sci Rev 170, 167–227 (2012). https://doi.org/10.1007/s11214-012-9902-4
O. Gasnault, S. Maurice, R. C. Wiens, S. Le Mouélic, W. W. Fischer, P. Caïs, K. McCabe, J.-M. Reess, and C. Virmontois "SUPERCAM REMOTE MICRO-IMAGER ON MARS 2020." - 46th Lunar and Planetary Science Conference (2015). https://www.hou.usra.edu/meetings/lpsc2015/pdf/2990.pdf
Telea, Alexandru. (2004). An Image Inpainting Technique Based on the Fast Marching Method. Journal of Graphics Tools. 9. 10.1080/10867651.2004.10487596. https://www.researchgate.net/publication/238183352_An_Image_Inpainting_Technique_Based_on_the_Fast_Marching_Method
Malvar, Henrique & He, Li-wei & Cutler, Ross. (2004). High-quality linear interpolation for demosaicing of Bayer-patterned color images. Acoustics, Speech, and Signal Processing, 1988. ICASSP-88., 1988 International Conference on. 3. iii - 485. 10.1109/ICASSP.2004.1326587. https://www.researchgate.net/publication/4087683_High-quality_linear_interpolation_for_demosaicing_of_Bayer-patterned_color_images
Getreuer, Pascal. (2011). Malvar-He-Cutler Linear Image Demosaicking. Image Processing On Line. 1. 10.5201/ipol.2011.g_mhcd. https://www.researchgate.net/publication/270045976_Malvar-He-Cutler_Linear_Image_Demosaicking
Maki, J.N., Gruel, D., McKinney, C. et al. The Mars 2020 Engineering Cameras and Microphone on the Perseverance Rover: A Next-Generation Imaging System for Mars Exploration. Space Sci Rev 216, 137 (2020). https://doi.org/10.1007/s11214-020-00765-9
Malin, M. C., et al. (2017), The Mars Science Laboratory (MSL) Mast cameras and Descent imager: Investigation and instrument descriptions, Earth and Space Science, 4, 506– 539, doi:10.1002/2016EA000252. https://doi.org/10.1002/2016EA000252
Di, K., and Li, R. (2004), CAHVOR camera model and its photogrammetric conversion for planetary applications, J. Geophys. Res., 109, E04004, doi:10.1029/2003JE002199. https://doi.org/10.1029/2003JE002199
Castano, A., Fukunaga, A., Biesiadecki, J. et al. Automatic detection of dust devils and clouds on Mars. Machine Vision and Applications 19, 467–482 (2008). https://doi.org/10.1007/s00138-007-0081-3
Dependencies
~24–37MB
~511K SLoC