Tone reproduction method by a local model of visual adaptation based on sigmoid function

In order to solve the dynamic range gap between image acquisition and display devices, tone reproduction algorithms are used to generate a visually similar mapping of input luminance to display luminance, which can be imported to realistic image rendition for ordinary images. The task is similar to visual adaptation processes in human visual system. Under different adaptation levels, human eyes have different contrast sensitivity and adaptation mechanisms to cope with high dynamic range scenes, where both too bright and too dark regions contained. So a realistic image rendition method by a local model of visual adaptation is proposed in this paper. The S-shape nonlinear mapping relationship is simulated by parameters controlled Sigmoid function, and its adaptive compression curves are achieved corresponding to various lightness adaptation levels. The method effectively keeps the balance between the wholly tone and luminance and local contrast, and enhances the visibility in dark region and keeps the detail in too bright region at the same time. Subjective assessment with objective featured statistical values is applied in the paper, it's approved that the method can effectively achieve high dynamic range compression, enhance image detail without artifacts, and it's computationally efficient and easy to use.