SMIL  0.10.6-dev
Image size

## Detailed Description Collaboration diagram for Image size:

## Functions

template<typename T >
RES_T resize (Image< T > &imIn, size_t sx, size_t sy, size_t sz, Image< T > &imOut, string algorithm="trilinear")
resize() - 3D image resize More...

template<typename T >
RES_T resize (Image< T > &imIn, size_t sx, size_t sy, Image< T > &imOut, string algorithm="trilinear")
resize() - 2D image resize More...

template<typename T >
RES_T resize (Image< T > &imIn, Image< T > &imOut, string algorithm="trilinear")
resize() - 3D image resize More...

template<typename T >
RES_T scale (Image< T > &imIn, double kx, double ky, double kz, Image< T > &imOut, string algorithm="trilinear")
scale() - 3D image scale (resize by a factor) More...

template<typename T >
RES_T scale (Image< T > &imIn, double kx, double ky, Image< T > &imOut, string algorithm="trilinear")
scale() - 2D image scale More...

template<typename T >
RES_T scale (Image< T > &imIn, double k, Image< T > &imOut, string algorithm="trilinear")
scale() - image scale (resize by a factor) More...

## ◆ resize() [1/3]

 RES_T smil::resize ( Image< T > & imIn, size_t sx, size_t sy, size_t sz, Image< T > & imOut, string algorithm = `"trilinear"` )

resize() - 3D image resize

Resize a 3D image - the value of each pixel in the output image is calculated from the input image after an interpolation algorithm.

There are two available algorithms :

• closest - this is the simpler algorithm. Pixel values in the output image are taken from the nearest corresponding pixel in the input image. This algorithm doesn't increases the number of possible values. So, it must be used when resizing binary images or images whose possible values shall be preserved in the output image.
• trilinear (extension of bilinear algorithm for 3D images) - this is the algorithm to use on gray level images.
Note
When algorithm is set to auto, the applied algorithm will be closest for binary images and trilinear or bilinear for gray level images
Parameters
 [in] imIn : input image [in] sx,sy,sz : dimensions to be set on output image [out] imOut : output image [in] algorithm : the interpolation algorithm to use. Can be trilinear (default), bilinear, closest or auto.

## ◆ resize() [2/3]

 RES_T smil::resize ( Image< T > & imIn, size_t sx, size_t sy, Image< T > & imOut, string algorithm = `"trilinear"` )

resize() - 2D image resize

Resize a 2D image - the value of each pixel in the output image is calculated from the input image after an interpolation algorithm.

Parameters
 [in] imIn : input image [in] sx,sy : dimensions to be set on output image [out] imOut : output image [in] algorithm : the interpolation algorithm to use. Can be trilinear (default), bilinear ou closest.

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

## ◆ resize() [3/3]

 RES_T smil::resize ( Image< T > & imIn, Image< T > & imOut, string algorithm = `"trilinear"` )

resize() - 3D image resize

Resize a 3D image - the value of each pixel in the output image is calculated from the input image after an interpolation algorithm.

The size of the output image is already set to what it should be.

Parameters
 [in] imIn : input image [out] imOut : output image [in] algorithm : the interpolation algorithm to use. Can be trilinear (default), bilinear ou closest.

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

## ◆ scale() [1/3]

 RES_T smil::scale ( Image< T > & imIn, double kx, double ky, double kz, Image< T > & imOut, string algorithm = `"trilinear"` )

scale() - 3D image scale (resize by a factor)

3D image scale - Scaling images is almost the same than resizing. Input parameters are the factors to multiply each dimension of the input image instead of the dimensions of output image.

There are two available algorithms :

• closest - this is the simpler algorithm. Pixel values in the output image are taken from the nearest corresponding pixel in the input image. This algorithm doesn't increases the number of possible values. So, it must be used when resizing binary images or images whose possible values shall be preserved in the output image.
• trilinear (extension of bilinear algorithm for 3D images) - this is the algorithm to use on gray level images.
Note
When algorithm is set to auto, the applied algorithm will be closest for binary images and trilinear or bilinear for gray level images
Parameters
 [in] imIn : input image [in] kx,ky,kz : scale factors [out] imOut : output image [in] algorithm : the interpolation algorithm to use. Can be trilinear (default), bilinear, closest or auto.

## ◆ scale() [2/3]

 RES_T smil::scale ( Image< T > & imIn, double kx, double ky, Image< T > & imOut, string algorithm = `"trilinear"` )

scale() - 2D image scale

3D image scale - Scaling images is almost the same than resizing. Input parameters are the factors to multiply each dimension of the input image instead of the dimensions of output image.

Parameters
 [in] imIn : input image [in] kx,ky : scale factors [out] imOut : output image [in] algorithm : the interpolation algorithm to use. Can be trilinear (default), bilinear ou closest.

## ◆ scale() [3/3]

 RES_T smil::scale ( Image< T > & imIn, double k, Image< T > & imOut, string algorithm = `"trilinear"` )

scale() - image scale (resize by a factor)

3D image scale - Scaling images is almost the same than resizing.
Input parameters are the factors to multiply each dimension of the input image instead of the dimensions of output image.

Parameters
 [in] imIn : input image [in] k : scale factor applied to each axis. [out] imOut : output image [in] algorithm : the interpolation algorithm to use. Can be trilinear (default), bilinear ou closest.