Abstract:
This paper proposes a two-step impulse noise suppression filter, in which detection is followed by filtering. Adaptive network-based fuzzy inference system (ANFIS) is use...Show MoreMetadata
Abstract:
This paper proposes a two-step impulse noise suppression filter, in which detection is followed by filtering. Adaptive network-based fuzzy inference system (ANFIS) is used in detection step and 3×3 median filter is used in filtering step. ANFIS employed is a good replacement of human expert. Our proposed method is time efficient and removes impulse noise while maintaining fine details of image.
Published in: IMPACT-2013
Date of Conference: 23-25 November 2013
Date Added to IEEE Xplore: 22 May 2014
ISBN Information:
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Grayscale Images ,
- Impulsive Noise ,
- Fuzzy Logic ,
- Time Efficiency ,
- Median Filter ,
- Noise Suppression ,
- Neural Network ,
- Denoising ,
- Filtered Based ,
- Feed-forward Network ,
- Membership Function ,
- Order Polynomial ,
- Image Noise ,
- Nodes In Layer ,
- Neighboring Pixels ,
- Central Pixel ,
- Human Visual System ,
- Noisy Images ,
- Detector Noise ,
- Noise Density ,
- Noisy Pixels ,
- Average Execution Time
Contents Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Grayscale Images ,
- Impulsive Noise ,
- Fuzzy Logic ,
- Time Efficiency ,
- Median Filter ,
- Noise Suppression ,
- Neural Network ,
- Denoising ,
- Filtered Based ,
- Feed-forward Network ,
- Membership Function ,
- Order Polynomial ,
- Image Noise ,
- Nodes In Layer ,
- Neighboring Pixels ,
- Central Pixel ,
- Human Visual System ,
- Noisy Images ,
- Detector Noise ,
- Noise Density ,
- Noisy Pixels ,
- Average Execution Time
