Full-Reference Objective Quality Assessment of Tone-Mapped Images

In this paper, we present a novel method for full-reference image quality assessment (IQA) of tone-mapped images displayed on standard low dynamic range (LDR) displays. Due to the dynamic range compression caused by the tone-mapping process, a mixture of several artifacts and distortions may be produced in the tone-mapped images. This makes the quality assessment of the tone-mapped images very challenging. Due to the diversity of such artifacts and distortions, we propose a bag of features (BOF) approach to tackle this problem. Specifically, in the proposed method, a number of different perceptually relevant quality-related features are first extracted from a given tone-mapped image and its reference HDR image. These features are designed such that they capture different aspects and attributes of the tone-mapped image such as its structural fidelity, naturalness, and overall brightness. A support vector regressor is then trained based on the extracted features, and it is used for measuring the visual quality of a tone-mapped image. Our experimental results indicate that the proposed method achieves high accuracy as compared to several existing methods.