Colored facial image restoration by similarity enhanced implicative fuzzy association memory - Kwang Baek Kim; Doo Heon Song (Institute of Advanced Engineering and Science, 2019)
Image restoration refers to the recovery of an underlying image from an observation that has been corrupted by various types of noise. In a digital forensic software, such image restoration process should be noise-tolerant, robust, fast, and scalable. In this paper, we apply implicative fuzzy association memory structure in colored facial image restoration with enhanced similarity measure involved in output computarion. The efficacy if the proposed fuzzy associative memory model is verified by the experiment in that it was 95% successful (with zero mean square error) out of 20 tested images.