This research proposes an Adaptive Weighted Fuzzy Mean Filter (AWFMF) based on Cloud Model (CM) to remove the salt and pepper noise in the digital images. Also, the performance of the proposed filter is compared with existing variants of median and switching filters using peak signal to noise ratio (PSNR) and quality index. The proposed filter is able to remove salt and pepper noise even at 90%...

In this paper, we investigate the signal-to-noise ratio (SNR) in the palm-sized multi-antenna communication systems. The presented analysis includes the mutual coupling on both, signal and thermal noise. We apply the Nyquist’s thermal noise theorem to determine the thermal noise behavior in the multi-antenna system and to confirm the partial correlation of thermal noise for antenna spacing lowe...

Image denoising has become an essential exercise in medical imaging especially the Magnetic Resonance Imaging (MRI). This paper proposes a medical image denoising algorithm using contourlet transform. Numerical results show that the proposed algorithm can obtained higher peak signal to noise ratio (PSNR) than wavelet based denoising algorithms using MR Images in the presence of AWGN.

This paper proposes a new procedure in order to improve the performance of block matching and 3-D filtering (BM3D) image denoising algorithm. It is demonstrated that it is possible to achieve a better performance than that of BM3D algorithm in a variety of noise levels. This method changes BM3D algorithm parameter values according to noise level, removes prefiltering, which is used in high nois...

An entropy-constrained residual vector quantization design algorithm is used to design codebooks for image coding. Entropy-constrained residual vector quantization has several important advantages. It can outperform entropy-constrained vector quantization in terms of rate-distortion performance, memory, and computation requirements. It can also be used to design vector quantizers with relativel...

In this paper, we propose a novel image denoising method by incorporating the dual-tree complex wavelets into the ordinary ridgelet transform. The approximate shift invariant property of the dual-tree complex wavelet and the high directional sensitivity of the ridgelet transform make the new method a very good choice for image denoising. We apply the digital complex ridgelet transform to denois...

In this paper an adaptive range and domain filtering is presented. In the proposed method local histograms are computed to tune the range and domain extensions of bilateral filter. Noise histogram is estimated to measure the noise level at each pixel in the noisy image. The extensions of range and domain filters are determined based on pixel noise level. Experimental results show that the propo...

This paper includes different approaches for adaptive wavelet threshold (Bayes Shrink and Normal Shrink) and a robust wavelet domain method for noise filtering in ultrasound images. The search for efficient image denoising methods is still a valid challenge at the crossing of functional analysis and statistics. The proposed work in this paper extends the existing technique by improving the thre...

--This paper presents a filter for restoration of Dental images that are highly corrupted by salt and pepper noise and speckle noise, Poisson noise. After detecting and correcting the noisy pixel, the proposed filter is able to suppress noise level. In this paper for each noise proposed different type of filter and compare these three types of filter with their PSNR value and MSE value and SNR ...

The most unique characteristic of the matched filter is that it produces the maximum achievable instantaneous SNR at its output when a signal plus additive white noise are present at the input. The noise does not need to be Gaussian. The peak instantaneous SNR at the receiver output can be achieved by matching the radar receiver transfer function to the received signal. We will show that the pe...