Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  introduces a novel approach for denoising the images corrupted by Impulsive Noise (IN) by using a new nonlinear IN suppression filter, entitled t-nearest neighborhood pixels based Adaptive-Fuzzy Filter (t-AFF). The proposed filter is based on statistical impulse detection and nonlinear filtering which uses Adaptive Neuro-Fuzzy Inference System as a missed data interpolant over the t-nearest neighbor pixels of the corrupted pixels. The impulse detection is realized by using the ll-known Edgington's goodness-of-fit test which yields a decision about the impulsivity of each pixel. To demonstrate the capability of t-AFF, extensive simulations re realized revealing that the proposed filter achieves a better performance than the other filters mentioned in this paper in the cases of being effective in noise suppression and detail preservation, even when the images are highly corrupted by IN.
['Pinar Civicioglu']
I am writing a research paper on a idea Using a neuro-fuzzy network for impulsive noise suppression from highly distorted images of WEB-TVs
[{"from": "human", "value": "I am writing a research paper on a idea Using a neuro-fuzzy network for impulsive noise suppression from highly distorted images of WEB-TVs"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  introduces a novel approach for denoising the images corrupted by Impulsive Noise (IN) by using a new nonlinear IN suppression filter, entitled t-nearest neighborhood pixels based Adaptive-Fuzzy Filter (t-AFF). The proposed filter is based on statistical impulse detection and nonlinear filtering which uses Adaptive Neuro-Fuzzy Inference System as a missed data interpolant over the t-nearest neighbor pixels of the corrupted pixels. The impulse detection is realized by using the ll-known Edgington's goodness-of-fit test which yields a decision about the impulsivity of each pixel. To demonstrate the capability of t-AFF, extensive simulations re realized revealing that the proposed filter achieves a better performance than the other filters mentioned in this paper in the cases of being effective in noise suppression and detail preservation, even when the images are highly corrupted by IN."}]