extract_radiometry: Extract radiometry data

In rcaiman: CAnopy IMage ANalysis

Extract radiometry data

Description

Extract radiometry from images taken with the aid of a portable light source and the calibration board detailed in calibrate_lens(). The end goal is to obtain the data required to model the vignetting effect.

Usage

extract_radiometry(l, size_px = NULL)

Arguments

l	List of prepossessed images (SpatRaster) for radiometry sampling. These images must comply with the equidistant projection.
size_px	Numeric vector of length one. Diameter in pixels of the circular sampling area at the image center. This area is modified considering the equidistant projection distortion. Therefore, it will be visualized as an ellipse at any other place but the image center.

Details

Lenses have the inconvenient property of increasingly attenuating light in the direction orthogonal to the optical axis. This phenomenon is known as the vignetting effect and varies with lens model and aperture setting. The method outlined here, known as the simple method, is explained in details in \insertCiteDiaz2024;textualrcaiman. Next explanation might serve mostly as a quick recap of it.

The development of the simple method was done with a Kindle Paperwhite eBooks reader of 6" with built-in light. However, an iPhone 6 plus was also tested in the early stages of development and no substantial differences were observed. A metal bookends desk book holder was used to fasten the eBook reader upright and a semi-transparent paper to favor a Lambertian light distribution. In addition, the latter was used to draw on in order to guide pixel sampling. The book holder also facilitated the alignment of the screen with the dotted lines of the printed quarter-circle.

As a general guideline, a wide variety of mobile devices could be used as light sources, but if scattered data points are obtained with it, then other light sources should be tested in order to double check that the light quality is not the reason for points scattering.

With the room only illuminated by the portable light source, nine photographs should be taken with the light source located in the equivalent to 0, 10, 20, 30, 40, 50, 60, 70, and 80 degrees of zenith angle, respectively. Camera configuration should be in manual mode and set with the aperture (f/number) for which a vignetting function is required. The shutter speed should be regulated to obtain light-source pixels with middle grey values. The nine photographs should be taken without changing the camera configuration or the light conditions.

This code exemplify how to use the function to obtain the data and base R functions to obtain the vignetting function (f_v).

.read_raw <- function(path_to_raw_file) {
  r <- read_caim_raw(path_to_raw_file, z, a, zenith_colrow,
                     radius = 500, only_blue = TRUE)
  r
}

l <- Map(.read_raw, dir("raw/up/", full.names = TRUE))
up_data <- extract_radiometry(l)
l <- Map(.read_raw, dir("raw/down/", full.names = TRUE))
down_data <- extract_radiometry(l)
l <- Map(.read_raw, dir("raw/right/", full.names = TRUE))
right_data <- extract_radiometry(l)
l <- Map(.read_raw, dir("raw/left/", full.names = TRUE))
left_data <- extract_radiometry(l)

ds <- rbind(up_data, down_data, right_data, left_data)

plot(ds, xlim = c(0, pi/2), ylim= c(0.5,1.05),
      col = c(rep(1,9),rep(2,9),rep(3,9),rep(4,9)))
legend("bottomleft", legend = c("up", "down", "right", "left"),
       col = 1:4, pch = 1)

fit <- lm((1 - ds$radiometry) ~ poly(ds$theta, 3, raw = TRUE) - 1)
summary(fit)
coef <- -fit$coefficients #did you notice the minus sign?
.fv <- function(x) 1 + coef[1] * x + coef[2] * x^2 + coef[3] * x^3
curve(.fv, add = TRUE, col = 2)
coef

Once one of the aperture settings is calibrated, it can be used to calibrate all the rest. To do so, the equipment should be used to take photographs in all desired exposition and without moving the camera, including the aperture already calibrated and preferably under an open sky in stable diffuse light conditions. The same procedure, which minor adaptations, is applicable to cross-camera calibration. Below code could be used as a template.

zenith_colrow <- c(1500, 997)*2
diameter <- 947*4
z <- zenith_image(diameter, c(0.689, 0.0131, -0.0295))
a <- azimuth_image(z)

files <- dir("raw/", full.names = TRUE)
l <- list()
for (i in seq_along(files)) {
  if (i == 1) {
    # because the first aperture was the one already calibrated
    lens_coef_v <- c(0.0302, -0.320, 0.0908)
  } else {
    lens_coef_v <- NULL
  }
  l[[i]] <- read_caim_raw(files[i], z, a, zenith_colrow,
                          radius = 500,
                          only_blue = TRUE,
                          lens_coef_v = lens_coef_v)
}

ref <- l[[1]]
rings <- rings_segmentation(zenith_image(ncol(ref), lens()), 3)
theta <- seq(1.5, 90 - 1.5, 3) * pi/180

.fun <- function(r) {
  r <- extract_feature(r, rings, return_raster = FALSE)
  r/r[1]
}

l <- Map(.fun, l)

.fun <- function(x) {
  x / l[[1]][] # because the first is the one already calibrated
}
radiometry <- Map(.fun, l)

l <- list()
for (i in 2:length(radiometry)) {
  l[[i-1]] <- data.frame(theta = theta, radiometry = radiometry[[i]][])
}
ds <- l[[1]]
head(ds)
# The result is one dataset (ds) for each file. This is all what it is needed
# before using base R functions to fit a vignetting function

Value

An object from the class data.frame with columns theta (zenith angle in radians) and radiometry (digital number (DN) or relative digital number (RDN), depending on argument z_thr.

References

\insertAllCited

See Also

Other Lens Functions: azimuth_image(), calc_diameter(), calc_relative_radius(), calc_zenith_colrow(), calibrate_lens(), crosscalibrate_lens(), expand_noncircular(), fisheye_to_equidistant(), fisheye_to_pano(), lens(), test_lens_coef(), zenith_image()

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