Improved Version of Tone-Mapped Quality Index
High Dynamic Range (HDR) images were evolved to display smallest details of the captured image with high standards. To display HDR images on Low Dynamic Range (LDR) monitors compression is required, which is done by Tone Mapping Operators (TMOs). Recently, there are a lot of tone mapping algorithms that are available in market. Different TMO creates images with different quality. To measure the quality of such images Tone-Mapped Quality Index was proposed (TMQI). TMQI mainly depends on the two parameters. The first is structural fidelity (SF) which is very similar to structural similarity and the second, is statistical naturalness (SN). The limitation of TMQI-1 is some parameter is image independent described in below sections so, improved model TMQI-2 is proposed in this paper. In order to further improve the quality of image, iterative optimization algorithm is used. Our experimental results show that TMQI-2 is better than earlier TMQI. Further, iterative optimization increases the overall quality of image.
KeywordsHigh dynamic range image Structural fidelity Statistical naturalness Tone mapping operator
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