Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6957690 | Signal Processing | 2018 | 26 Pages |
Abstract
Tone-mapping operators (TMOs) can be used to transform the data format of high-dynamic-range (HDR) images to traditional low-dynamic-range (LDR) image data format. Hence, the performance of a TMO is crucial for applying HDR images in widely-used LDR image processing systems at this stage. In this work, we propose an exposure condition analysis based quality assessment method for tone-mapped HDR images. Firstly, a purpose-designed HDR exposure segmentation model was used to divide HDR images by analyzing local exposure property. Then, we extracted two new low-complexity quality features (abnormal exposure ratio and exposure residual energy) and a color-based feature in different exposure regions. Finally, the quality assessment model was obtained by regression training. Experiments demonstrate the ability of our method to predict the quality of tone-mapped HDR images. The Pearson linear correlation coefficients are higher than 0.88; thus, the proposed method is highly consistent with human visual perception.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Song Yang, Jiang Gangyi, Yu Mei, Peng Zongju, Chen Fen,