resize {EBImage}R Documentation

Spatial linear transformations

Description

The following functions perform all spatial linear transforms: reflection, rotation, translation, resizing, and general affine transform.

Usage

flip(x)
flop(x)
rotate(x, angle, filter="bilinear", output.dim, output.origin=c(0, 0))
translate(x, v, filter="none", output.dim)
resize(x, w, h, filter="bilinear", output.dim, output.origin=c(0, 0))
affine(x, m, filter=c("bilinear", "none"), output.dim)

Arguments

x

An Image object or an array.

angle

A numeric specifying the image rotation angle in degrees.

filter

A character string indicating the interpolating sampling filter. Valid values are 'none' or 'bilinear'. See Details.

output.dim

A vector of 2 numbers indicating the dimension of the output image. Default is dim(x) in all transforms except in resize, where it is c(w, h).

output.origin

A vector of 2 numbers indicating the output coordinates of the origin in pixels. Default is c(0, 0).

v

A vector of 2 numbers denoting the translation vector in pixels.

w, h

Width and height of the resized image. One of these arguments can be missing to enable proportional resizing.

m

A 3x2 matrix describing the affine transformation. See Details.

Details

flip transforms x in its vertical mirror image by reflecting the pixels around the central x-axis.

flop transforms x in its horizontal mirror image by reflecting the pixels around the central y-axis.

rotate rotates the image counter-clockwise with the specified angle, centered on the input image center. Rotation center is changed by modifying the argument output.origin.

resize resizes the image x to desired dimensions. Resizing center is changed by modifying the argument output.origin. Zooming, without changing the output dimension, is achieved by setting the arguments w and h to values different from output.dim.

affine returns the affine transformation of x, where pixels coordinates, denoted by the matrix px, are transformed to cbind(px, 1)%*%m.

All spatial transforms excepted flip and flop are based on the general affine transformation. Spatial interpolation could be of two type: none, also called nearest neighbor, where interpolated pixel value is computed by taking the closest pixel, or bilinear, where interpolated pixel is computed by bilinear approximation of the 4 neighboring pixels. The bilinear filter gives the smoother results.

Value

An Image object or an array, containing the transformed version of x.

Author(s)

Gregoire Pau, 2012

See Also

transpose

Examples

  x <- readImage(system.file("images", "lena.png", package="EBImage"))
  if (interactive()) display(x)

  y <- flip(x)
  if (interactive()) display(y, title='flip(x)')

  y = flop(x) 
  if (interactive()) display(y, title='flop(x)')

  y <- resize(x, 128) 
  if (interactive()) display(y, title='resize(x, 128)')

  y <- rotate(x, 30) 
  if (interactive()) display(y, title='rotate(x, 30)')

  y <- translate(x, c(120, -20)) 
  if (interactive()) display(y, title='translate(x, c(120, -20))')

  m <- matrix(c(0.6, 0.2, 0, -0.2, 0.3, 300), nrow=3)
  if (interactive()) display(affine(x, m), title='affine transform')
[Package EBImage version 4.4.0 Index]