Getting Started with cuvis.r

Overview

cuvis.r provides R bindings to the Cubert CUVIS C SDK for reading, processing, and exporting hyperspectral imaging data from Cubert snapshot cameras. It mirrors the API of cuvis.python.

Prerequisites

Install the Cubert CUVIS SDK (>= 3.4.0) from https://cloud.cubert-gmbh.de/s/qpxkyWkycrmBK9m
Set the CUVIS_SDK environment variable to the SDK install directory
Install cuvis.r from GitHub:

remotes::install_github("cttir/cuvis.r")

Quick Start

Initialize the SDK

Every cuvis.r session begins with cuvis_init() and ends with cuvis_shutdown():

library(cuvis.r)

cuvis_init()

Load a Session File

Cubert cameras store measurements in .cu3s session files. Load one with cuvis_session():

session <- cuvis_session("path/to/measurement.cu3s")
print(session)

Extract a Measurement

Session files contain one or more measurements. Access them by index (1-based):

mesu <- cuvis_get_measurement(session, 1)
print(mesu)

Inspect Metadata

md <- cuvis_get_metadata(mesu)
md$name
md$integration_time
md$serial_number
md$product_name

Get the Data Cube

The hyperspectral data cube is returned as a 3D R array [rows, cols, bands] with wavelength metadata attached:

# First, process to generate the cube
ctx <- cuvis_processing_context(session)
cuvis_reprocess(ctx, mesu, mode = "raw")

cube <- cuvis_get_cube(mesu)
dim(cube)                        # e.g., c(100, 100, 61)
attr(cube, "wavelengths")        # wavelengths in nm

You can subset bands, compute means, or use standard R array operations:

# Mean reflectance per band
band_means <- apply(cube, 3, mean, na.rm = TRUE)

# Extract a single band (e.g., band 30)
single_band <- cube[, , 30]
image(single_band, main = "Band 30")

Export to Standard Formats

# ENVI format (widely supported by remote sensing tools)
cuvis_export_envi(mesu, "output/envi/")

# Multi-channel TIFF
cuvis_export_tiff(mesu, "output/tiff/")

Shutdown

cuvis_shutdown()

Next Steps

See vignette("cuvis-r-calibration") for the full calibration workflow (dark/white references, reflectance conversion)
See the cuvis.python examples for workflow patterns that translate directly to cuvis.r