Locally adaptive demosaicing technique for security images based upon region-of-interest analysis

This paper presents the novel demosaicing approach that is based upon region of interest analysis. The question of if only the reconstruction quality of areas where human gazes during identification process of security objects are crucial for quality of identification is solved. Two fixation density maps were constructed on the basis of the ground through visual attention data which was acquired during an eye tracking experiment. Two security scenes containing traffic signs were used as testing images. SSIM and VIF with subjective testing were used for evaluation of reconstruction quality. The results tackle the questions - if quality of identification mainly depends on the quality of the areas where human eye is attracted, areas of interest, and whether the quality of the remaining part of image perceived by peripheral vision is crucial for quality of identification. Furthermore, the results show that embedding the information relating to these visual fixation patterns into demosaicing procedure can preserve the perceived image quality and quality of identification, while the computational complexity of proposed approach can be low.