awsraw {adimpro}R Documentation

Smoothing and demosaicing of RAW images

Description

The function integrates smoothing and demosaicing of RAW image data.

Usage

awsraw(object, hmax = 4, aws = TRUE, wb = c(1, 1, 1), cspace = "Adobe", ladjust = 1, maxrange=TRUE,
lkern = "Triangle", graph = FALSE, max.pixel = 400, compress = TRUE)

Arguments

object an object of class adimpro containing the RAW image data. See read.raw for creating such objects.
hmax maximal bandwidth to use in the smoothing algorithm.
aws use adaptive weights if aws==TRUE.
wb Vector containing factors for the three color chanels, allows to change the white balance.
cspace Color space of the result,
ladjust Factor for the kritical value \lambda. Defaults to 1, smaller values increase sensitivity but may result in isolated noisy pixel. Values larger than 1 give smoother up to cartoon like results.
maxrange If TRUE increase range of values to maximum.
lkern Specifies the location kernel. Defaults to "Triangle", other choices are "Quadratic", "Cubic" and "Uniform". The use of "Triangle" corresponds to the Epanechnicov kernel nonparametric kernel regression.
graph (logical). If graph=TRUE intermediate results are illustrated after each iteration step. Defaults to FALSE.
max.pixel Maximum dimension of images for display if graph=TRUE. If the true dimension is larger, the images are downscaled for display. See also show.image.
compress logical, determines if image data are stored in raw-format.

Details

Adaptive smoothing is performed on the original RAW data, restricting positive weights to pixel corresponding to the same color channel. Noise is assumed to have a variance depending linearly on the mean. Weights are determined by weigthed distances between color vectors. These color vectors are obtained by demosaicing that is applied to the smoothed RAW data after each iteration of the smoothing algorithm. The demosaicing algorithm is a 3D generalized median, see method="Median4" in function develop.raw.

Value

Object of class "adimpro"

img Contains the reconstructed image.
ni Contains the sum of weights, i.e. trace(W_i), in all grid points i.
ni0 Contains the maximum sum of weights for an nonadaptive kernel estimate with the same bandwidth.
hmax Bandwidth used in the last iteration.
call The arguments of the function call.
varcoef Estimated coefficients in the linear variance model for the color channels.

Author(s)

Karsten Tabelow tabelow@wias-berlin.de and Joerg Polzehl polzehl@wias-berlin.de

References

Polzehl, J. and Tabelow, K. (2007). Adaptive smoothing of digital images, Journal of Statistical Software 19 (1).

See Also

\code{read.raw},\code{awsimage}, \code{make.image}, \code{show.image}, \code{clip.image}

Examples

## Not run: demo(raw)

[Package adimpro version 0.7.1 Index]