Fast tone mapping operator for high dynamic range image using prior information

This paper presents a fast tone mapping operator (TMO) that effectively reproduces high dynamic range (HDR) images on common displays while maintaining visual appeal. The proposed method addresses the trade-off between computational complexity and detail retention inherent in existing global and local TMOs by leveraging prior information. We construct a dynamic range compression model on the HDR luminance channel and introduce two priors to fast generate the low dynamic range (LDR) luminance channel. First, most local regions of the inverted LDR luminance channel have some very low intensity pixels. Second, the luminance of the global light layer is a constant. Besides, we propose an adaptive luminance normalization approach based on the brightness feature of the input HDR image, facilitating the stability of tone mapping performance. Detail enhancement and color attenuation techniques are also presented to improve local contrasts and manage over-saturation. The effectiveness of the proposed TMO is validated through comparison with state-of-the-art methods. Both subjective and objective results show that our method outperforms others in producing high-quality tone-mapped images. Additionally, it exhibits lower computational complexity than local TMOs while remaining comparable to global ones.