We propose a simple and fast algorithm called PatchLift for computing distances between patches (contiguous block of samples) extracted from a given one-dimensional signal. PatchLift is based on the observation that the patch distances can be efficiently computed from a matrix that is derived from the one-dimensional signal using lifting; importantly, the number of operations required to comput...

A novel exemplar-based image inpainting algorithm using the Non-Local Means (NLM) algorithm and Criminisi algorithm is proposed. In order to decrease the error in match rate, the new algorithm adopts the sum of squared differences (SSD) search method for several exemplars to generate a candidate exemplar set. Then it determines the Hausdorff distance as measurement criterion to find a match blo...

The speckle is omnipresent in synthetic aperture radar (SAR) images as an intrinsic characteristic. However, it is unwanted in certain applications. Therefore, intelligent filters for speckle reduction are of great importance. It has been demonstrated in several literatures that the non-local means filter can reduce noise while preserving details. This paper discusses non-local means filter for...

Real-time cardiac MRI appears as a promising technique to evaluate the mechanical function of the heart. However, ultra-fast MRI acquisitions come with an important signal-to-noise ratio (SNR) penalty, which drastically reduces the image quality. Hence, a real-time denoising approach would be desirable for SNR amelioration. In the clinical context of cardiac dysfunction assessment, long acquisi...

In this paper, investigation report is prepared on various approach for noise decrease and improvement of very low-light video. A general methodology for noise reduction and contrast improvement in very noisy image information with low dynamic vary is given. In color image information, the color property is restored and demosaicing of raw RGB input data is performed at the same time with the no...

In this paper, we propose a new framework to remove parts of the systematic errors affecting popular restoration algorithms, with a special focus for image processing tasks. Generalizing ideas that emerged for `1 regularization, we develop an approach re-fitting the results of standard methods towards the input data. Total variation regularizations and non-local means are special cases of inter...

Delineation and noise removal play a significant role in clinical quantification of PET images. Conventionally, these two tasks are considered independent, however, denoising can improve the performance of boundary delineation by enhancing SNR while preserving the structural continuity of local regions. On the other hand, we postulate that segmentation can help denoising process by constraining...

Neural networks are a computational paradigm model of the human brain that has become popular in recent years. We have tried to address the problem of Gliomaby creating a more accurate classifier which can act as an expert assistant to medical practitioners. Brain stem gliomas are now recognized as a heterogenous group of tumors. In this paper, proposed a prediction of Glioma in MR images using...

A direct implementation of the bilateral filter requires O(σs) operations per pixel, where σs is the (effective) width of the spatial kernel. A fast implementation of the bilateral filter was recently proposed that require O(1) operations per pixel with respect to σs. This is done by using trigonometric functions for the range kernel of the bilateral filter, and by exploiting their so-called sh...

Image denoising is an integral component of many practical medical systems. Non-local means (NLM) is an effective method for image denoising which exploits the inherent structural redundancy present in images. Improved adaptive non-local means (IANLM) is an improved variant of classical NLM based on a robust threshold criterion. In this paper, we have proposed an enhanced non-local means (ENLM)...