Non-uniformity correction of infrared images by midway equalization
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#include <vector>
Go to the source code of this file.
Functions | |
float * | MIRE (float[], float, int, int) |
void | MIRE_automatic (float[], int, int, int, int, float) |
Arguments : image, std-dev of the gaussian, image size. | |
float | TV_column_norm (float[], int, int, float) |
Arguments : image, image size, sigma_min,simga_max,sigma_step: | |
void | specify_column (float[], int, int, int, std::vector< float >) |
Arguments : image, image size. | |
float | gaussian (int, float) |
Arguements : imge, image size, column to be processed, target values. | |
std::vector< std::vector< float > > | target_histogram (std::vector< std::vector< float > >, int, int, float) |
Arguements : position (in pixel), std-dev. | |
std::vector< std::vector< float > > | column_sorting (float[], int, int) |
Arguments : vector of vector containing the sorted values, image size,sigma. | |
std::vector< float > | histo_column (float[], int, int, int) |
Arguments : image, image size. |
std::vector<std::vector<float> > column_sorting | ( | float | [], |
int | , | ||
int | |||
) |
Arguments : vector of vector containing the sorted values, image size,sigma.
float gaussian | ( | int | x, |
float | sigma | ||
) |
Arguements : imge, image size, column to be processed, target values.
Arguements : imge, image size, column to be processed, target values.
x | point of evaluation |
sigma | std-dev of the gaussian |
Definition at line 219 of file MIRE.cpp.
std::vector<float> histo_column | ( | float | [], |
int | , | ||
int | , | ||
int | |||
) |
Arguments : image, image size.
float* MIRE | ( | float | [], |
float | , | ||
int | , | ||
int | |||
) |
void MIRE_automatic | ( | float | [], |
int | , | ||
int | , | ||
int | , | ||
int | , | ||
float | |||
) |
Arguments : image, std-dev of the gaussian, image size.
void specify_column | ( | float | [], |
int | , | ||
int | , | ||
int | , | ||
std::vector< float > | |||
) |
Arguments : image, image size.
std::vector<std::vector<float> > target_histogram | ( | std::vector< std::vector< float > > | V_HISTOS, |
int | w1, | ||
int | h1, | ||
float | sigma | ||
) |
Arguements : position (in pixel), std-dev.
Arguements : position (in pixel), std-dev.
V_HISTOS | vector containing sorted columns. |
w1 | image width |
h1 | image height |
sigma | std-dev of the Gaussian. |
Compute the midway Gaussian averaged histogram. Gaussian weighted, troncated with radius equal to 4 sigma: only the columns in the interval ["column"-4sigma, "column"+4sigma] are taken into account. Input: image, column current, std-dev sigma Output : Midway-gaussian-averaged histogram (vector).
Implemented in 3 steps: Step1 : extract columns columns in the interval ["column"-4sigma, "column"+4sigma] Step2 : Sort all vectors obtained from step1 separately Step3 : for all lines and all column of step2 compute the midway gaussian averaged ie : v(i)=WEIGHT(column).*(paquet(ligne,column)));
Definition at line 316 of file MIRE.cpp.
float TV_column_norm | ( | float | [], |
int | , | ||
int | , | ||
float | |||
) |
Arguments : image, image size, sigma_min,simga_max,sigma_step: