An Enhanced Two-Stage Impulse Noise Removal Technique based on Fast ANFIS and Fuzzy Decision
نویسنده
چکیده
Image enhancement plays a vital role in various applications. There are many techniques to remove the noise from the image and produce the clear visual of the image. Moreover, there are several filters and image smoothing techniques available in the literature. All these available techniques have certain limitations. Recently, neural networks are found to be a very efficient tool for image enhancement. A novel two-stage noise removal technique for image enhancement and noise removal is proposed in this paper. In noise removal stage, Adaptive Neuro-Fuzzy Inference System (ANFIS) with a Modified Levenberg-Marquardt training algorithm was used to eliminate the impulse noise. The usage of Modified LevenbergMarquardt training algorithm will reduce the execution time. In the image enhancement stage, the fuzzy decision rules inspired by the Human Visual System (HVS) are used to categorize the image pixels into human perception sensitive class and nonsensitive class, and to enhance the quality of the image. The Hyper trapezoidal fuzzy membership function is used in the proposed technique. In order to improve the sensitive regions with higher visual quality, a Neural Network (NN) is proposed. The experiment is conducted with standard image. It is observed from the experimental result that the proposed FANFIS shows significant performance when compared to existing methods. Keywords--Fuzzy Decision, Impulse Noise, Peak Signal to Noise Ratio (PSNR), Modified Levenberg-Marquardt Training Algorithm, Adaptive Neuro-Fuzzy Inference System
منابع مشابه
A Hybrid Filtering Technique for Eliminating Uniform Noise and Impulse Noise on Digital Images
A new hybrid filtering technique is proposed to improving denoising process on digital images. This technique is performed in two steps. In the first step, uniform noise and impulse noise is eliminated using decision based algorithm (DBA). Image denoising process is further improved by an appropriately combining DBA with Adaptive Neuro Fuzzy Inference System (ANFIS) at the removal of uniform no...
متن کاملAn Enhanced Median Filter for Removing Noise from MR Images
In this paper, a novel decision based median (DBM) filter for enhancing MR images has been proposed. The method is based on eliminating impulse noise from MR images. A median-based method to remove impulse noise from digital MR images has been developed. Each pixel is leveled from black to white like gray-level. The method is adjusted in order to decide whether the median operation can be appli...
متن کاملA Hybrid Filtering Technique for Eliminating Gaussian Noise and Impulse Noise on Digital Images
A new hybrid filtering technique is proposed to improving denoising process on digital images. This technique is performed in two steps. In the first step, gaussian noise and impulse noise is eliminated using decision based algorithm (DBA). Image denoising process is further improved by an appropriately combining DBA with Adaptive Neuro Fuzzy Inference System (ANFIS) at the removal of gaussian ...
متن کاملA Hybrid Filtering Technique for Random Valued Impulse Noise Elimination on Digital Images
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 ...
متن کامل