introduction: an efficient method of tomographic imaging in nuclear medicine is positron emission tomography (pet). compared to spect, pet has the advantages of higher levels of sensitivity, spatial resolution and more accurate quantification. however, high noise levels in the image limit its diagnostic utility. noise removal in nuclear medicine is traditionally based on fourier decomposition o...

Bilateral filter and Total variation image denoising are widely used in image denoising. In low noisy level, bilateral filtering is better than TV denoising for it reveals better SNR and sharper edges. However, in high noisy level, TV denoising outperforms bilateral filtering in terms of SNR and more details of non edges. It is very difficult to perform denoising of a very noisy image for the r...

This paper proposes an Adaptive Image Denoising Method based on Thresholding that follows the similar approach as in the NeighShrink method. This method shrinks the noisy wavelet coefficients using an adaptive threshold. The NeighShrink and its versions namely, IAWDMBNC and IIDMWT always produce unfavourable smoothing of edges and details of the noisy image because these methods kill more noisy...

A major problem in noisy image processing is the segmentation of its components. Many computer vision tasks analyze regions after segmenting a given image, then minimize the segmentation error to build a good automatic inspection system. In this paper, we propose a novel segmentation scheme for noisy images which consists of a new denoising method and a modified active contour model. The method...

Image denoising is getting more significance, especially in Computed Tomography (CT), which is an important and most common modality in medical imaging. This is mainly due to that the effectiveness of clinical diagnosis using CT image lies on the image quality. The denoising technique for CT images using window-based Multi-wavelet transformation and thresholding shows the effectiveness in denoi...

We first describe how to “fuzzify” the estimated binary columns to create a [0,1]-valued column. Werefer to this [0,1] -valued column as the soft segmentation column of the noisy spectrogram column.Similarly to the collection of soft segmentation columns as the soft segmentation image, or simply asthe soft segmentation. The band-dependent posterior probability that the hard segmentation columnv...

Over the past decade, there has been significant interest in fractal coding for the purpose of image compression. However, applications of fractal-based coding to other aspects of image processing have received little attention. We propose a fractal-based method to enhance and restore a noisy image. If the noisy image is simply fractally coded, a significant amount of the noise is suppressed. H...

Remote sensing is defined as obtaining information about a Performance metrics for measuring absolute degradation and their gain in fused image quality are proposed when fusing noisy input modalities. This considers fusion of noise patterns, is also developed and used to evaluate the perceptual effect of noise corrupting homogenous image regions (i.e. areas with no salient features). These metr...

This paper describes the participation of UAIC team at the ImageCLEF 2011 competition, Wikipedia Retrieval task. The aim of the task was to investigate retrieval approaches in the context of a large and heterogeneous collection of images and their noisy text annotations. We submitted a total of six runs, focusing our effort along the textual retrieval, query expansion on English language, combi...