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Other signal-processing related operations


Functions

void Convolution (Image< T > &input1, Image< T > &input2, Image< T > &output)
void Downsample (Image< T > &input, Image< T > &output)
void Downsample (Image< T > &input)
void Noise (Image< T > &input, string noise_type, float a, float b, int seed=1)
void Noise (Image< T > &input, int seed=1)
void Noise (Image< T > &input, float a, float b, int seed=1)
void Noise (Image< T > &input, string noise_type, int seed=1)
void Upsample (Image< T > &input, Image< T > &output)
void Upsample (Image< T > &input)

Detailed Description

This group contains stand-alone functions implementing convolution, downsampling, upsampling, and noise addition.

Function Documentation

void Convolution ( Image< T > & input1,
Image< T > & input2,
Image< T > & output )
 

Performs the convolution of two images (input1 and input2) and stores the result in a third image (output). Note that if the operands are of type \aT = \afloat (floating point image or floating point kernel), or of the derived types "FloatImage" and/or "FloatKernel", the convolution operation is performed as multiplication in Fourier space (for speed-up reasons).

Examples:
test_convol.cpp.

Definition at line 17 of file Convolution.cpp.

void Downsample ( Image< T > & input )
 

Performs in place the downsampling of the input image.

Definition at line 23 of file Downsampling.cpp.

void Downsample ( Image< T > & input,
Image< T > & output )
 

Performs the downsampling of the input image and stores the result in the output image.

Examples:
test_downsampl.cpp.

Definition at line 12 of file Downsampling.cpp.

void Noise ( Image< T > & input,
string noise_type,
int seed = 1 )
 

Adds noise of type noise_type to the input image. Three types of noise are allowed:

  • Gaussian noise with mean 0 and standard deviation 1. For this purpose the parameter noise_type should be "normal".
  • Noise with uniform distribution in the interval [0, 1]. For this purpose the parameter noise_type should be "uniform".
  • Salt and pepper noise. For this purpose the parameter noise_type should be "salt&pepper". The percentage of the image pixels that are affected by the noise is randomly chosen.
The "seed" parameter is used to initialize the random generator. Its default value is 1.

Definition at line 53 of file Noise.cpp.

void Noise ( Image< T > & input,
float a,
float b,
int seed = 1 )
 

Adds Gaussian noise with mean a and standard deviation b to the input image.

The parameter seed is used to initialize the random generator. Its default value is 1.

Definition at line 48 of file Noise.cpp.

void Noise ( Image< T > & input,
int seed = 1 )
 

Adds Gaussian noise with mean 0 and standard deviation 1 to the input image.

The parameter seed is used to initialize the random generator. Its default value is 1.

Definition at line 43 of file Noise.cpp.

void Noise ( Image< T > & input,
string noise_type,
float a,
float b,
int seed = 1 )
 

Adds noise of type noise_type to the input image. Three types of noise are allowed:

  • Gaussian noise with mean "a" and standard deviation "b". For this purpose the parameter noise_type should be "normal".
  • Noise with uniform distribution in the interval [a, b]. For this purpose the parameter noise_type should be "uniform".
  • Salt and pepper noise. For this purpose the parameter noise_type should be "salt&pepper". The parameter a indicates what percentage of the image pixels are affected by the noise. The parameter b is ignored.
The parameter seed is used to initialize the random generator. Its default value is 1.
Examples:
test_noise.cpp.

Definition at line 18 of file Noise.cpp.

void Upsample ( Image< T > & input )
 

Performs the upsampling of the input image in place.

Definition at line 23 of file Upsampling.cpp.

void Upsample ( Image< T > & input,
Image< T > & output )
 

Performs the upsampling of the input image and stores the result in the output image.

Examples:
test_upsampl.cpp.

Definition at line 12 of file Upsampling.cpp.