Gradient magnitude similarity for tone-mapped image quality assessment

Abstract

Recently, high dynamic range (HDR) image which can accurately reflect the real scene prompts increasing interest. For visualizing the HDR images on standard display devices, it is needed to convert it to low dynamic range (LDR) images. This process is named as tone-mapping. Due to the reduction of the dynamic range, evaluating the tone-mapped image becomes important. Gradient magnitude measure has been used in many state-of-the-art image quality assessment methods. In our research we find that the gradient magnitude measure is also effective for the quality assessment of tone-mapped images. The more different between the gradient magnitude maps of the HDR image and the corresponding LDR image, the worse quality of the LDR image. This paper using the gradient magnitude feature develops a gradient magnitude based method for tone-mapped image quality assessment. The similarity of gradient magnitude maps between the HDR image and the corresponding LDR image is computed. A tone-mapped image should look natural. The naturalness measure used in tone-mapped image quality index (TMQI) is as the supplement measure. In the experiment on the subject-rated tone-mapped image database provided by the authors of TMQI, our proposed method gets better performance than state-of-the-art tone-mapped image assessment methods.