FSITM: A Feature Similarity Index For Tone-Mapped Images

Abstract

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.

4 Pages, 1 Figure, 1 Table

Cited by in corpus (5)

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• Deep Tone Mapping Operator for High Dynamic Range Images
• Blind High Dynamic Range Quality estimation by disentangling perceptual and noise features in images
• Quality Assessment for Tone-Mapped HDR Images Using Multi-Scale and Multi-Layer Information
• Perceptual Tone Mapping Model for High Dynamic Range Imaging