Conventional contrast enhancement methods, including global and local enhancements, produce enhanced images with some limitations. Global contrast enhancement does not take the local characteristics into consideration, and therefore, the enhancement performance could be limited. On the other hand, a local contrast enhancement method achieves a noticeable improvement, but it generates unnatural improvement results compared with the input image. Due to the complementary characteristics of these two methods, it is hard to achieve remarkable contrast enhancement without visual artifacts. To overcome the limitations, we propose a new tone mapping function for contrast enhancement using an optimization approach that is subject to constraints such as the output image needing to be enhanced naturally and noticeably. Since contrast enhancement without artificiality is possible when the enhancement process mimics the human eye, we model the human visual perception system, and then, the model is incorporated into the proposed tone mapping function. Consequently, the contrast of the image is adaptively enhanced according to a region that is more attractive to a person. The experimental results demonstrate that the proposed algorithm outperforms other contrast enhancement methods in terms of both objective and subjective criteria.