Among various kinds of image denoising methods, the Perona–Malik model is a representative Partial Differential Equation based (PDE-based) algorithm which effectively removes the noise as well as having edge enhancement simultaneously through anisotropic diffusion controlled by the diffusion coefficient. However, the unstable behavior of the Perona–Malik model introduces staircasing artifacts i...

In this paper, we present the use of a generic image segmentation method, namely a succession of Random Forest classifiers in an autocontext framework, for the MICCAI 2014 Challenge on Endocardial 3D Ultrasound Segmentation (CETUS). The proposed method segments each frame independently in 90 sec, without requiring temporal information such as end-diastolic or end-systolic time points nor any re...

This paper introduces a novel method for noise reduction in medical images based on concepts of the Non-Local Means algorithm. The main objective has been to develop a method that optimizes the processing speed to achieve practical applicability without compromising the quality of the resulting images. A database consisting of prototypes, composed of pixel neighborhoods originating from several...

In this article, we propose a super-resolution method to resolve the problem of image low spatial because of the limitation of imaging devices. We make use of the strong nonlinearity mapped ability of the back-propagation neural networks(BPNN). Training sample images are got by undersampled method. The elements chose as the inputs of the BPNN are pixels referred to Non-local means(NL-Means). Ma...

In this paper, we propose a fast algorithm called PatchLift for computing distances between patches extracted from a one-dimensional signal. PatchLift is based on the observation that the patch distances can be expressed in terms of simple moving sums of an image, which is derived from the one-dimensional signal via lifting. We apply PatchLift to develop a separable extension of the classical N...

Patch-based methods used in digital image processing fields are generally able to produce effective results. Although these approaches use easier structures to achieve better visual quality in digital image restoration compared with other methods, research is still going on in the field. In this study, a better noise reduction approach is presented using a patch-based algorithm in the wavelet d...

We present a stereo image denoising algorithm. Our algorithm takes as an input a pair of noisy images of an object captured from two different directions (stereo images). We use either Maximum Difference or Singular Value Decomposition similarity metrics for identifying locations of similar searching windows in the input images. We adapt the Non-local Means algorithm for denoising collected pat...

The recently introduced non-local means (NLM) image denoising technique broke the traditional paradigm according to which image pixels are processed by their surroundings. Non-local means technique was demonstrated to outperform state-of-the art denoising techniques when applied to images in the visible. This technique is even more powerful when applied to low contrast images, which makes it tr...

In this paper, we present an innovative mechanism for image restoration problems in which the is corrupted by a mixture of additive white Gaussian noise (AWGN) and impulse (IN). Mixed removal much more challenging problem contrast to where either only one type model (either or impulse) involved. Several well-known efficient algorithms exist effectively remove Impulse noise, independently. Howev...