A Hybrid Filtering Technique for Random Valued Impulse Noise Elimination on Digital Images
نویسندگان
چکیده
A novel adaptive network fuzzy inference system (ANFIS) based filter is presented for the enhancement of images corrupted by random valued impulse noise (RVIN). This technique is performed in two steps. In the first step, impulse noise using an Asymmetric Trimmed Median Filter (ATMF). In the second step, image restoration is obtained by an appropriately combining ATMF with ANFIS at the removal of higher level of RVIN on the digital images. Three well known images are selected for training and the internal parameters of the neuro-fuzzy network are adaptively optimized by training. This technique offers excellent line, edge, and fine detail preservation performance while, at the same time, effectively enhancing digital images. Extensive simulation results were realized for ANFIS network and different filters are compared. Results show that the proposed filter is superior performance in terms of image denoising and edges and fine details preservation properties.
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