mahmoudnafifi / APAP-bias-correction-for-illumination-estimation-methods

Bias correction method for illuminant estimation -- JOSA 2019

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As-projective-as-possible bias correction for illumination estimation algorithms

Mahmoud Afifi1, Abhijith Punnappurath1, Graham Finlayson2, and Michael S. Brown1

1York University, Canada

2The University of East Anglia, UK

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main figure

How to use:

1- In main.m file, select the dataset from 'dataset' variable, the initial estimation method from 'ill_method' variable, and the correction method from 'method' variable.

You can use your own dataset and/or your own initial estimation by using dataset='other'; ill_method ='yourMethodName'; but, remember to add your method name to the switch case in projective_biasCorrection.m file.

Also make sure that your file contains a field with your illuminant estimation method. More information is given in main.m file.

2- Run main.m

The main procedure is performed in 'projective_biasCorrection' function which has the followings parameters:

-data: a structure that contains the following fields:

1- gt: Nx3 ground truth illuminant vectors

2- illuminant_method_name: Nx3 initial estimated illuminant vectors. I.e., the variable should be named with the illuminant method name.

-ill_method: a string of the illuminant method name. It should match the name of the filed in the data struct.

-method: it can be 'P', 'APAP', or 'APAP-LUT'

-param: method parameters

To add your own method, please update the switch case (line 100) in projective_biasCorrection.m with your method name.


Please cite the following work if this program is used: Mahmoud Afifi, Abhijith Punnappurath, Graham Finlayson, and Michael S. Brown, As-projective-as-possible bias correction for illumination estimation algorithms, Journal of the Optical Society of America A (JOSA A), Vol. 36, No. 1, pp. 71-78, 2019

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Bias correction method for illuminant estimation -- JOSA 2019

License:MIT License


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