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Low-dose computed tomography (LDCT) images tend to be severely degraded by excessive mottle noise and steak artifacts. In this paper, an algorithm of modified smooth patch ordering (MSPO) is proposed to improve the LDCT images. In the MSPO method, the non-local means (NLM) algorithm is modified by replacing the Leclerc robust function with the modified bisquare robust function, to serve as weight...
Block Compressed Sensed (BCS) images reconstructed by the Smoothed Projected Landweber (SPL) equations are severely degraded in visual quality. This work focuses on removal of the noise present in the BCS - SPL reconstructed image. For noise removal the nature of the noise is studied first. A suitable frequency domain filter to mitigate this noise is proposed in this work. Differential Pulse Coded...
Oversampled transforms are useful tools for data analysis, since redundancy increases freedom in the choice of the processing. We propose here a framework for oversampled lapped transform of images. More specifically, we establish conditions for perfect reconstruction of 2D data using non-separable windows. We also provide an example of a transform which relies on this approach. We also show the benefit...
Depth maps generated by Kinect cameras often contain a significant amount of missing pixels and strong noise, limiting their usability in many computer vision applications. In this paper we present an efficient hole filling and damaged region restoration method that improves the quality of the depth maps obtained with the Microsoft Kinect device. The proposed approach based on a modified exemplar-based...
In this letter, an approach based on spectral diversity and conventional Interferometric Synthetic Aperture Radar (InSAR) for Digital Elevation Model (DEM) reconstruction is proposed. Conventional InSAR technique often fails to correctly reconstruct the DEM due to the presence of discontinuities and/or interferometric noise. With the assistance of the spectral diversity method, the ill-posed phase-unwrapping...
It turns out that the iterative approach is very attractive for image reconstruction in positron emission tomography (PET). Its reconstruction quality heavily depends on the accuracy of the measurement model, which consists of the projection matrix and the statistics of noise. Almost all of iterative approaches require that the projection matrix is exactly known a prior, which conflicts with the fact...
Detection of pixels corrupted by noise and assessing the degree to which the pixels are corrupted intrinsically fuzzy processes, involve uncertainty and imprecision. The paper aims at reconstruction of the image with ensured quality after removing noise from the original image. Here region marking process has been introduced to obtain number of clusters automatically which partition the whole image...
This paper presents a plausible real-time smooth mesh generation method from real scene images, captured from a conventional color and depth camera. We perform statistical outlier removal method to detect holes for the captured raw depth image and fill the detected holes with the weighted mean values of its neighbors. The 3D surface mesh of the real scene is then reconstructed. The initially generated...
Noise is ever-present in communication channels and can produce devastating degradation to the images at the receiver end. In this paper, a novel approach to detecting different types of noise models in corrupted images is presented. Basically, it is a two-step process that has the ability to handle real-time applications due to its computational simplicity. The proposed algorithm handles error correction...
In this paper a modified simple edge preserved denoising algorithm to remove salt and pepper noise in digital color images is presented. The algorithm has three steps: noisy pixel detection, replacement of noisy pixels, confirmation by comparing with a threshold. In additon a median filtering is added to improve the qualityof the image. The proposed algorithm prevents the smoothing of edges in the...
A 2D signal is often used as an image signal in the application of a digital image, which could produce noise in the processing of image acquisition. It is too rough of a traditional method to be used for noise suppression; regarding noise suppression, it will also lose part of the original signal so that makes the image blurred. This paper introduces image reduction based on the wavelet analysis...
Medical applications of ultrasound imaging have expanded enormously over the last two decades. De-noising is challenging issues for better medical interpretation and diagnosis on high volume of data sets in echocardiography. In this paper, manifold learning algorithm is applied on 2-D echocardiography images to discover the relationship between the frames of consecutive cycles of the heart motion...
In this paper, we propose a spatially adaptive noise removal algorithm using local statistics that consists of two stages: noise detection and removal. To corporate desirable properties into denoising process, the local weighted mean, local weighted activity, and local maximum are defined. With these local statistics, the noise detection function is defined and a modified Gaussian filter is used to...
The first-order differential invariants of optic flow, namely divergence, curl, and deformation, provide useful shape indicators of objects passing through view. However, as differential quantities these are often difficult to extract reliably. In this paper we present a filter-based method for computing these invariants with sufficient accuracy to permit the construction of a partial scene model...
Phase measurement is a key step in quantitative optical metrology. While phase shifting technique is widely applied for accurate and reliable static or semi-static phase measurement, Fourier and wavelet transforms are often employed for high speed dynamic phase measurement. In our previous papers, the authors had proposed an alternative clustering method for dynamic phase measurement. The proposed...
The effect of the image filter using SVD directly is strongly restricted by image interclass orientation and noise characteristic. By simulation and analysis, this paper present that not only the singular values but also the singular vectors are sensitive to above mentioned factors. And a method using the sensitivity is proposed to evaluate and select appropriate filtering methods quantitatively....
This paper proposes a new morphological filter for SAR interferograms. It is based on a modified version of alternate sequential filters with reconstruction (MASF), in which the structuring elements are adaptively defined according to the fringe directions. This provides a good fidelity to the fringe information while efficiently removing noise. Another feature of the proposed approach is to apply...
In this paper, we propose a novel super-resolution image reconstruction algorithm to handle license plate texts in real traffic videos. A generalized discontinuity adaptive Markov random field (DAMRF) model is proposed based on the recently reported bilateral filtering, which is not only edge preservation but also robust to noise. Moreover, instead of looking for fixed value for the regularization...
Watershed transformation is a common technique for image segmentation. However, its use for medical image segmentation has been limited particularly due to over-segmentation. In response to the characteristics of medical image, especially the contour extraction from the MRI (magnetic resonance imaging) brain image, this paper proposes an improved method in order to overcome the drawbacks. Firstly,...
Automatic fingerprint recognition has received considerable attention over the past decades. Progress has been made on models of the structures of fingerprints, techniques for acquisition of prints, and the developments of commercial automated fingerprint identification systems. Despite these advances, there remain considerable opportunities for improvements. The speed of retrieval and the ability...
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