Images functionalities that need resampling


Functions

cpl_image * cpl_image_extract_subsample (const cpl_image *image, int xstep, int ystep)
 Sub-sample an image.
double cpl_image_get_interpolated (const cpl_image *source, double xpos, double ypos, const cpl_vector *xprofile, double xradius, const cpl_vector *yprofile, double yradius, double *pconfid)
 Interpolate a pixel.
cpl_error_code cpl_image_warp (cpl_image *out, const cpl_image *in, const cpl_image *deltax, const cpl_image *deltay, const cpl_vector *xprofile, double xradius, const cpl_vector *yprofile, double yradius)
 Warp an image.
cpl_error_code cpl_image_warp_polynomial (cpl_image *out, const cpl_image *in, const cpl_polynomial *poly_u, const cpl_polynomial *poly_v, const cpl_vector *xprofile, double xradius, const cpl_vector *yprofile, double yradius)
 Warp an image according to a 2d polynomial transformation.

Detailed Description

This module provides functions to warp images.

Synopsis:
   #include "cpl_image_resample.h"

Function Documentation

cpl_image* cpl_image_extract_subsample ( const cpl_image *  image,
int  xstep,
int  ystep 
)

Sub-sample an image.

Parameters:
image The image to subsample
xstep Take every xstep pixel in x
ystep Take every ystep pixel in y
Returns:
The newly allocated sub-sampled image or NULL in error case
See also:
cpl_image_extract
xstep and ystep shall be positive.

Currently xstep must equal ystep.

step represents the sampling step in x and y: a step of 2 will create an image with a qaurter of the pixels of the input image.

Currently, both the X- and Y-size of the image must be divisible by the step.

image type can be CPL_TYPE_INT, CPL_TYPE_FLOAT and CPL_TYPE_DOUBLE.

The returned image must be deallocated using cpl_image_delete().

Possible _cpl_error_code_ set in this function:

double cpl_image_get_interpolated ( const cpl_image *  source,
double  xpos,
double  ypos,
const cpl_vector *  xprofile,
double  xradius,
const cpl_vector *  yprofile,
double  yradius,
double *  pconfid 
)

Interpolate a pixel.

Parameters:
source Interpolation source
xpos Pixel x floating-point position (FITS convention)
ypos Pixel y floating-point position (FITS convention)
xprofile Interpolation weight as a function of the distance in X
xradius Positive inclusion radius in the X-dimension
yprofile Interpolation weight as a function of the distance in Y
yradius Positive inclusion radius in the Y-dimension
pconfid Confidence level of the interpolated value (range 0 to 1)
Returns:
The interpolated pixel value, or undefined on error
See also:
cpl_image_get()
If the X- and Y-radii are identical the area of inclusion is a circle, otherwise it is an ellipse, with the larger of the two radii as the semimajor axis and the other as the semiminor axis.

The radii are only required to be positive. However, for small radii, especially radii less than 1/sqrt(2), (xpos, ypos) may be located such that no source pixels are included in the interpolation, causing the interpolated pixel value to be undefined.

The X- and Y-profiles can be generated with cpl_vector_fill_kernel_profile(profile, radius). For profiles generated with cpl_vector_fill_kernel_profile() it is important to use the same radius both there and in cpl_image_get_interpolated().

A good profile length is CPL_KERNEL_DEF_SAMPLES, using radius CPL_KERNEL_DEF_WIDTH.

On error *pconfid is negative (unless pconfid is NULL). Otherwise, if *pconfid is zero, the interpolated pixel-value is undefined. Otherwise, if *pconfid is less than 1, the area of inclusion is close to the image border or contains rejected pixels.

The input image type can be CPL_TYPE_INT, CPL_TYPE_FLOAT and CPL_TYPE_DOUBLE.

Here is an example of a simple image unwarping (with error-checking omitted for brevity):

const double xyradius = CPL_KERNEL_DEF_WIDTH;

cpl_vector * xyprofile = cpl_vector_new(CPL_KERNEL_DEF_SAMPLES); cpl_image * unwarped = cpl_image_new(nx, ny, CPL_TYPE_DOUBLE);

cpl_vector_fill_kernel_profile(xyprofile, CPL_KERNEL_DEFAULT, xyradius);

for (iv = 1; iv <= ny; iv++) { for (iu = 1; iu <= nx; iu++) { double confidence; const double x = my_unwarped_x(); const double y = my_unwarped_y();

const double value = cpl_image_get_interpolated(warped, x, y, xyprofile, xyradius, xyprofile, xyradius, &confidence);

if (confidence > 0) cpl_image_set(unwarped, iu, iv, value); else cpl_image_reject(unwarped, iu, iv); } }

cpl_vector_delete(xyprofile);

Possible _cpl_error_code_ set in this function:

cpl_error_code cpl_image_warp ( cpl_image *  out,
const cpl_image *  in,
const cpl_image *  deltax,
const cpl_image *  deltay,
const cpl_vector *  xprofile,
double  xradius,
const cpl_vector *  yprofile,
double  yradius 
)

Warp an image.

Parameters:
out Pre-allocated image to hold the result
in Image to warp.
deltax The x shifts for each pixel
deltay The y shifts for each pixel
xprofile Interpolation weight as a function of the distance in X
xradius Positive inclusion radius in the X-dimension
yprofile Interpolation weight as a function of the distance in Y
yradius Positive inclusion radius in the Y-dimension
Returns:
CPL_ERROR_NONE or the relevant _cpl_error_code_ on error
See also:
cpl_image_get_interpolated()
'out' and 'in' can have different sizes. The 'out' image pixels positions correspond to the lower left pixels positions in the 'in' image. In other words, the ID transformation would write the lower left part of 'in' in 'out'.

deltax and deltay must be of type CPL_TYPE_DOUBLE and of the same size as out. For each pixel, the deltax and deltay are such that:

  X = x + deltax
  Y = y + deltay
  

where (X,Y) is the position in the 'out' image, (x,y) is the position in the 'in' image

FIXME: Flux-calibration is missing.

Beware that extreme transformations may lead to blank images.

The input image type can be CPL_TYPE_INT, CPL_TYPE_FLOAT and CPL_TYPE_DOUBLE.

Examples of profiles and radius are:

  xprofile = cpl_vector_new(CPL_KERNEL_DEF_SAMPLES) ;
  cpl_vector_fill_kernel_profile(profile, CPL_KERNEL_DEFAULT,
        CPL_KERNEL_DEF_WIDTH) ;
  xradius = CPL_KERNEL_DEF_WIDTH ;
  

Possible _cpl_error_code_ set in this function:

cpl_error_code cpl_image_warp_polynomial ( cpl_image *  out,
const cpl_image *  in,
const cpl_polynomial *  poly_u,
const cpl_polynomial *  poly_v,
const cpl_vector *  xprofile,
double  xradius,
const cpl_vector *  yprofile,
double  yradius 
)

Warp an image according to a 2d polynomial transformation.

Parameters:
out Pre-allocated image to hold the result
in Image to warp.
poly_u 2D Polynomial transform in U.
poly_v 2D Polynomial transform in V.
xprofile Interpolation weight as a function of the distance in X
xradius Positive inclusion radius in the X-dimension
yprofile Interpolation weight as a function of the distance in Y
yradius Positive inclusion radius in the Y-dimension
Returns:
CPL_ERROR_NONE or the relevant _cpl_error_code_ on error
See also:
cpl_image_get_interpolated()
'out' and 'in' can have different sizes. The 'out' image pixels positions correspond to the lower left pixels positions in the 'in' image. In other words, the ID transformation would write the lower left part of 'in' in 'out'.

Warp an image according to a polynomial transform. Provide two 2d cpl_polynomial poly_u and poly_v such as:

  x = cpl_polynomial_eval(pu, (u, v))
  y = cpl_polynomial_eval(pv, (u, v))
  

Attention! The polynomials define a reverse transform. (u,v) are coordinates in the warped image and (x,y) are coordinates in the original image. The transform you provide is used to compute from the warped image, which pixels contributed in the original image.

FIXME: Flux-calibration is missing.

Beware that extreme transformations may lead to blank images.

The input image type can be CPL_TYPE_INT, CPL_TYPE_FLOAT and CPL_TYPE_DOUBLE.

The two images may have different dimensions and types.

Possible _cpl_error_code_ set in this function:


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