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FSITM: A Feature Similarity Index For Tone-Mapped Images

2017-04-19 · Hossein Ziaei Nafchi, Atena Shahkolaei, Reza Farrahi Moghaddam, Mohamed Cheriet

In this work, based on the local phase information of images, an objective index, called the feature similarity index for tone-mapped images (FSITM), is proposed. To evaluate a tone mapping operator (TMO), the proposed index compares the locally weighted mean phase angle map of an original high dynamic range (HDR) to that of its associated tone-mapped image calculated using the output of the TMO method. In experiments on two standard databases, it is shown that the proposed FSITM method outperforms the state-of-the-art index, the tone mapped quality index (TMQI). In addition, a higher performance is obtained by combining the FSITM and TMQI indices. The MATLAB source code of the proposed metric(s) is available at https://www.mathworks.com/matlabcentral/fileexchange/59814.

📄 PDF Abstract BibTeX arXiv:1704.05624

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Tone Mapping

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