With the growing popularity of High Dynamic Range Imaging (HDRI), the necessity for advanced tone-mapping techniques has greatly increased. In this thesis, I propose a novel saliency guided edge-preserving tone-mapping method that uses saliency region information of an HDR image as input to a guided filter for base and detail image layer separation. Both high resolution and low resolution saliency maps were used for the performance evaluation of the proposed method. After detail layer enhancement and base layer compression with constant weights, a new edge preserved tone-mapped image was composed by adding the layers back together with saturation and exposure adjustments. The filter operation is faster due to the use of the guided filter, which has O(N) time operation with N number of pixels. Both objective and subjective quality assessment results demonstrated that the proposed method has higher edge and naturalness preserving capability, which is homologous to the Human Visual System (HVS), as compared to other state-of-the-art tone-mapping approaches.
Human Visual System Model-Based Optimized Tone Mapping of High Dynamic Range Images
