In digital image different kinds of noises exist in an image and a variety of noise reduction techniques are available to perform de-noising. Selection of the de-noising algorithm depends on the types of noise. Gaussian noise, speckle noise, salt & pepper noise, shot noise are types of noises that are present in an image. The principle approach of image de-noising is filtering. Available filter...

Image de-noising and clustering in medical images are quite complex because of narrow dynamic range and in-homogeneity. Pre processing steps like image de-noising do have influence over the subsequent image processing which misleads further image analysis. In this paper, a new method which incorporates the advantages of adaptive center weighted median filter and hybrid median filter, called Ite...

Image Preprocessing is a vital step in the field of image processing for biometric pattern recognition. This paper studies and reviews various classical and modern fingerprint image de-noising models. The various model used for de-noising ranges widely from transform matrix using frequency, histogram model denoising, de-noising by introducing Gabor filter and its types to enhance fingerprint im...

Unlike Gaussian noise, Rician noise filtering is more challenging, since this type of noise exists in Functional Magnetic Resonance Imaging (fMRI) data which makes the analysis of fMRI data very difficult for experimental and clinical purposes. To cope with the situation, normally (smoothing) de-noising is done before the analysis of the data using conventional methods like Gaussian filtering a...

As to the hybrid noise characteristic, a mixed de-noising method is hereby proposed in combination with the median filter and the wavelet transform. Firstly, conduct the median filter to the pending image; then apply an improved threshold function to the wavelet transform (WT) to eliminate noise; finally, adopt Signal Noise Ratio (SNR) to evaluate the image de-noising effect. The experiment res...

The details of an image with noise may be restored by removing noise through a suitable image de-noising method. In this research, a new method of image de-noising based on using median filter (MF) in the wavelet domain is proposed and tested. Various types of wavelet transform filters are used in conjunction with median filter in experimenting with the proposed approach in order to obtain bett...

De-noising and extraction of the weak signature are crucial to fault prognostics in which case features are often very weak and masked by noise. The wavelet transform has been widely used in signal de-noising due to its extraordinary time-frequency representation capability. In this paper, the performance of wavelet decomposition-based de-noising and wavelet filter-based de-noising methods are ...

Through the analyzing of limitations on wavelet threshold filter de-noising, this paper applies wavelet filter based on compressed sensing to reduce the signal noise of spectral signals, and compares the two methods through experiments. The results of experiments shown that the wavelet filter based on compressed sensing can effectively reduce the signal noise of spectral signal. The de-noising ...

Because the classic intersecting cortical model (ICM) and the traditional image de-noising algorithm exist the deficiencies-the image collection, transmission and conversion are often subjected to impulse noise interference, thus affecting the quality of the image, therefore we improved the framework structure and related parameters of the ICM and proposed the adaptive image de-noising algorith...

Tracking problem in spherical coordinates with range rate (Doppler) measurements, which would have errors correlated to the range measurement errors, is investigated in this paper. The converted Doppler measurements, constructed by the product of the Doppler measurements and range measurements, are used to replace the original Doppler measurements. A de-noising method based on an unbiased Kalma...