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The inverse problem of fluorescence diffuse optical tomography (FDOT) is often highly ill-posed, which needs regularization techniques. In this paper, we propose a combined l1-l2-norm regularization method to address the ill-posed FDOT inverse problem. Compared with the traditional Tikhonov regularization, the proposed method is able to effectively remove the noise in the reconstructed image without...
Background Modeling is the normal method on the moving objects detection, it plays a key role in the moving objects detection and tracking, the Gaussian mixture model is one of the most successful methods on the detection. But it converges slowly in the complex scene. This paper proposes a new method named “additive increase” and the “additive decrease” to adjust the weight of the matched distributions...
Melanoma can be cured if it is detected early, so early diagnosis is very important in dermatological practice today. Early and non-invasive diagnosis of melanomas can be done by accurate image segmentation of skin lesions. The medical images, while acquisition are generally bound to contain noise. This paper proposes a robust and efficient image segmentation algorithm using LOG edge detector to extract...
This paper presents the evaluation of the effect of noise reduction techniques on the brain Computed Tomography (CT) images. In particular, multiscale geometric denoising methods based on curvelet transform are used and compared with wavelet based methods. The simulated results show that cycle spinning based curvelet transform method outperforms the wavelet based methods not only for the suppression...
This paper presents a methodology of using Kalman filter to minimize the error in stereo vision based distance measurement data (3D position of pedestrians). In stereo vision, little point mis-correspondence leads to a very bad estimate of depth during triangulation. There are robust correspondence algorithms but all of them suffer from algorithm complexity affecting the time performance. If simple...
In the field of image processing, it is inevitable to contain various noises in the image signals obtaining by the CCD camera. CCD noise model is a combination of a mixture of a fixed-pattern noise and multiplicative Gaussian noise and a mixture of signal-independent noise. Based on the model, this paper proposed a method to remove the noise from digital images corrupted by CCD device. The method...
Improving quality of noisy images has been an active area of research in many years. It has been shown that wavelet thresholding methods had better results than classic approaches. However estimation of threshold and selection of thresholding function are still the challenging tasks. In this paper, a new thresholding function is proposed for wavelet thresholding. This function is continues and has...
Wavelet-based denoising has comprehensive functionalities including feature extraction and low-pass filtering, while keeping characteristics such as low entropy, multi-resolution, irrelevance, etc. Wavelet-based denoising methods have been successfully applied for image processing in varieties. However, one of the main factors degrading underwater imaging is the backward scattered light, which performs...
The singular points in signal often include some important information, whose detection and localization have significance in many practical problems. In this paper, according to the relationship between the singular points in signal and the maximum absolute value of the signal wavelet transform, the noise can be deleted through the maximum absolute value iteration. The effectiveness of deleting noise...
Image processing is an important area in the information industry. A crucial research is how to filter noise caused by the nature, system and processing of transfers and so on. The noise mixed with the useful images or signals and brings the researchers lots of troubles. In many research areas related, such as target detecting and tracking, edge detecting and image registration, image denoising is...
Mainstay of this paper is to reduce noise to perform video enhancement using filtered directional bases and frequency-adaptive shrinkage. The input image is decomposed into flat region and edge region. After removing noise in the flat region, noise in the edge region is removed. We present a new directional transform using wavelet basis and Gaussian low pass filters. Hence after the removal of noise,...
In this paper, Spatial video denoising using wavelet transform has been focussed as it requires less computation and more suitable for real-time applications. Two specific techniques for spatial video denoising using wavelet transform are considered in this work, 2D Discrete Wavelet Transform (2D DWT) and Integer wavelet transform. Each of these techniques has its advantages and disadvantages. The...
Gel electrophoresis (GE) is an important tool in genomic analysis. It is a process of DNA, RNA and protein molecules separation using electric field applied to a gel matrix. This paper describes the image processing techniques applied on GE image to segment the bands from their background. Numerous pre-processing steps are applied on the image prior to the segmentation technique for the purpose of...
In this paper we propose a denoising method under the powerful framework-non local means (NL-means), in conjunction with regression analysis. First, the conception and development of NL-means is proposed. Second, an image important area map (IIAM) is calculated for the protection of edge and structure regions during denoising. Therefore, improved version of NL-means is carried out, which uses a novel...
In medical image processing, image denoising has become a very essential for better information extraction from the image and mainly from so noised ones, such as ultrasound (US)images. On the other hand, processed image must preserve the pertinent details of the primary image. So, arbitration between the perpetuation of useful diagnostic information and noise suppression must be teasured in medical...
Recently we developed a periodic modeling approach for determining the optical flow in a periodic image sequence, which is demonstrated to be beneficial for noise reduction in motion-compensated 4D reconstruction of cardiac gated images. In this approach, a Fourier harmonic model is used to exploit the temporal continuity and periodicity of the motion field in the sequence. In this work, we further...
We develop optimal forward and inverse variance-stabilizing trans formations for the Rice distribution, in order to approach the problem of magnetic resonance (MR) image filtering by means of standard denoising algorithms designed for homoskedastic observations. Further, we present a stable and fast iterative procedure for robustly estimating the noise level from a single Rician-distributed image...
In this paper we introduce a new algorithm for reconstruction of low-dose CT images. The approach, called multi-resolution feature fusion (MRFF), combines the textural qualities of conventional filtered-back projection images, with the noise suppression ability of non-quadratic regularized iterative reconstructions, to form a fast image reconstruction with good noise texture properties. Low-dose abdominal...
Several methods of phase retrieval for in line phase tomography have already been investigated based on the linearization of the relation between the phase shift induced by the object and the diffracted intensity. They use the Transport Intensity Equation (TIE) or the Contrast Transfer Function (CTF), or mixed approaches. In this work, we present a non linear iterative approach using the Frechet derivative...
Denoising is amongst the most challenging steps involved in analyzing fMRI data. The conventionally used Gaussian smoothing improves the SNR at the cost of spatial sensitivity and specificity. We briefly describe a 3-D framework for wavelet based fMRI analysis that includes denoising and signal separation followed by a detailed illustration of the benefits and improvements when applied to multi-group...
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