A Fast HDR Image TMO based on a Simplified Eye Sensitivity Model

Tone mapping is essential for displaying High Dynamic Range (HDR) images on Low Dynamic Range (LDR) screens. The quality performance of these algorithms has improved greatly over recent times, however their computational complexity has also considerably increased. Real-time applications are constrained because of this limitation in their deployment. Therefore, a fast tone-mapping algorithm is presented that maintains the same quality level as state-of-the-art techniques but has a considerably lower computational complexity. Based on an existing well-known Threshold vs. Intensity (TVI) model, a simplified human eye sensitivity model is derived that leads to a non-iterative method of TMO construction. The proposed model is used to construct a histogram of the HDR image such that the bins vary in size in the spatial domain but each of them covers the same amount of change in the luminance perceived by the human eye. Moreover, a simple yet effective solution is suggested to the over-enhancement and over-compression problems faced by histogram-based techniques. The proposed architecture is computationally light, hardware-friendly, produces superior visual results, and works significantly faster than state-of-the-art techniques.