Image noise removal is most important pre-processing step of image processing. Filtering method is emphasized for all types of de-noising schemes used for noise removal. In this paper, we have study about the different methods based on non-linear filter to remove the impulse noise from images. Different image noise removal algorithms are studied and some parameters are compared in a wide range ...

One of the key issues in removing random-valued impulse noise from digital images using switching filters is the impulse noise detection. Impulse noise is a random, spiked variation in the brightness of the image. In this paper, a new impulse noise detection algorithm is presented that is based on Noise ratio Estimation and a combination of K-means clustering and Non-Local Means based filter (N...

The characteristics of impulse bursts in remote sensing images are analyzed and a model for this noise is proposed. The model also takes into consideration other noise types, for example, the multiplicative noise present in radar images. As a case study, soft morphological filters utilizing a training-based optimization scheme are used for the noise removal. Different approaches for the trainin...

This paper presents one simple and novel technique for removal of impulse noise from corrupted image data. The algorithm involves impulse detection followed by spatial filtering of the corrupted pixels. In this method the presence of impulse noise is detected by a simpler method called a fuzzy logic based technique (FLT). However, the filtering idea is to recover the healthy pixel by the help o...

An efficient noise reduction approach is proposed by combining Robust Outlyingness Ratio (ROR) which measures how impulse like each pixel is, with noise adaptive fuzzy switching median filter (NAFSM) and fuzzy c-means (FCM) segmentation. Based on the ROR values all the pixels are divided into four levels. Then in the coarse and fine stage introduce the NAFSM filter that optimizes the performanc...