colorfulness: Quantify colorfulness

In rcaiman: CAnopy IMage ANalysis

Quantify colorfulness

Description

Quantify the colorfulness of an image

Usage

colorfulness(caim, m = NULL)

Arguments

caim	SpatRaster. The return of a call to read_caim() or read_caim_raw().
m	SpatRaster. A mask. For hemispherical photographs, check mask_hs(). Default (NULL) is the equivalent to enter !is.na(caim$Red).

Details

Quantify the colorfulness of an sRGB image using a bidimensional space formed by the green/red and the blue/yellow axes of the CIE LAB space, symbolized with A and B, respectively. The colorfulness index (CI) is defined as

CI = \dfrac{A_o}{A_p} \cdot 100,

where A_o and A_p are the observed and potential area of the AB plane. A_o refers to the colors from the image while A_p to the colors from the whole sRGB cube.

Value

A numeric vector of length one.

Note

An early version of this function was used in \insertCiteMartin2020;textualrcaiman.

References

\insertAllCited

See Also

Other Tool Functions: correct_vignetting(), defuzzify(), extract_dn(), extract_feature(), extract_rl(), extract_sky_points_simple(), extract_sky_points(), extract_sun_coord(), find_sky_pixels_nonnull(), find_sky_pixels(), masking(), optim_normalize(), percentage_of_clipped_highlights(), read_bin(), read_caim_raw(), read_caim(), write_bin(), write_caim()

Examples

caim <- read_caim() %>% normalize()
colorfulness(caim)

rcaiman documentation built on Nov. 15, 2023, 1:08 a.m.