The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper aims in presenting a thorough comparison of performance and usefulness of de-noising techniques, belonging to scale-space domain. Multi-scale Transform (MST) based image de-noising techniques overcome the limitation of Fourier based methods, as it provides the local and detailed information of non stationary image at different scales, which is necessary for de-noising process. The MST based...
Image denoisig is becoming an essential step for analysis of images which occurs due to the imperfections of sensors or during the transmission of data. A novel algorithm for image denoising is proposed, based on fuzzy logics. Using fuzzy features an algorithm is primed which adaptively removes impulse noises. This algorithm consists of two parts including the detection of noise and the removal of...
We propose a fast, local denoising method where the Euclidean curvature of the noisy image is approximated in a regularizing manner and a clean image is reconstructed from this smoothed curvature. User preference tests show that when denoising real photographs with actual noise our method produces results with the same visual quality as the more sophisticated, nonlocal algorithms Non-local Means and...
Image denoising is an issue in image processing, constantly spawning ideas to better deal with this problem. Both the Fourier and Wavelet domains remove noise, but have their own weaknesses. A hybrid Fourier-Wavelet Neighborhood Coefficient method is proposed, with experiments showing that the effectiveness of this method is greater than the previous hybrid Fourier-Wavelet neighborhood approach.
Images acquired and processed in communication and multimedia systems are often noisy. Thus, pre-filtering is a typical stage to remove noise. At this stage, a special attention has to be paid to image visual quality. This paper analyzes denoising efficiency from the viewpoint of visual quality improvement using metrics that take into account human vision system (HVS). Specific features of the paper...
This paper embeds SSIM in place of the L2 norm in a one step Non Local Means (NLM) scheme. This is possible thanks to a new form of SSIM that can be formally derived from the classical SSIM using the spreading error analysis. This approach has several advantages over L2 norm based NLM such as greater robustness to parameters setting, higher performance in terms of PSNR and SSIM, optimal subjective...
When our gaze fixates a point, the visual acuity is maximal at the fixation point (imaged by the fovea, i.e. the central part of the retina) and decreases rapidly towards the periphery of the visual field. This phenomenon is known as foveated vision or foveated imaging. We recently investigated the role of fovation in image filtering and we have shown that the foveated patch distance, i.e. the Euclidean...
In this paper, the relative intersection of confidence intervals (ICI) rule is used to adaptively determine window sizes around each observed point in purpose of denoising. The relative ICI rule defines neighbourhoods of similar statistical properties for every signal sample. If we calculate a mean value on each window, it corresponds to the zero-order estimation and results in a denoised signal....
This paper presents a new adaptive approach for image denoising with Gaussian noise based on a combination of the Bidimensional Empirical Mode Decomposition (BEMD) and the the discrete wavelet transforms (DWT). The BEMD is an auto-adaptive method for the analysis of nonlinear or non-stationary signals and images. The input image is decomposed into several modes called Intrinsic Mode Functions (IMFs),...
Ultrasound imaging is a widely used and safe medical diagnostic technique; however, the usefulness of ultrasound imaging is degraded by the presence of signal dependant noise known as speckle. In this paper, we propose a new speckle reduction method and coherence enhancement of ultrasound images based on method that combines total variation (TV) method and wavelet shrinkage. In our method, a noisy...
In order to discriminate normal and abnormal heart sounds (HSs) accurately and effectively, a new method for clinical diagnosis of the heart valve diseases is proposed. The method is composed of three stages. The first stage is the preprocessing stage. During the pre-processing stage, the improved wavelet threshold shrinkage denoising algorithm is used for the noise reduction of the measured HSs....
In this paper we proposed a new technique for detects and removes impulse noise in grayscale digital images. Proposed method work in two steps, in first step we detect noisy pixels using fuzzy reasoning with lowest uncertainty, and in second step we replace noisy pixels with a heuristic median filter, our heuristic median's filter is combined with human knowledge for select best replacement. We analysis...
Current approaches to automatic, class specific, image retrieval from the World Wide Web (WWW) by linguistic query often make use of an image's internal characteristics and file meta-data to augment and improve result accuracy. We propose that, in extension, improvement can be achieved in relevance, noise-reduction and completeness through sense disambiguation and contextual meta-data prepossessing...
As one of the best image denoising methods, the Non-Local Means(NL-Means)algorithm[5] proposed by Buades et al. generates state-of-the-art performance. However, due to the high computational complexity, it is difficult to be directly used in practical applications. In this paper, a novel fast algorithm based on the similarity of spatially sampled pixels is introduced. Compared with other fast approaches,...
This paper presents a novel bilateral filtering using fuzzy-median for image manipulations such as denoising and tone mapping. Our proposed bilateral filtering consists of the standard bilateral filter and the estimation of the pixel values by the fuzzy median filter. We have applied the proposed fuzzy filtering for image denoising with both the impulse and Gaussian random noise, which achieves better...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.