Search results for "NOISE REDUCTION"
showing 10 items of 71 documents
Multispectral image denoising with optimized vector non-local mean filter
2016
Nowadays, many applications rely on images of high quality to ensure good performance in conducting their tasks. However, noise goes against this objective as it is an unavoidable issue in most applications. Therefore, it is essential to develop techniques to attenuate the impact of noise, while maintaining the integrity of relevant information in images. We propose in this work to extend the application of the Non-Local Means filter (NLM) to the vector case and apply it for denoising multispectral images. The objective is to benefit from the additional information brought by multispectral imaging systems. The NLM filter exploits the redundancy of information in an image to remove noise. A …
Fast Distributed Subspace Projection via Graph Filters
2018
A significant number of linear inference problems in wireless sensor networks can be solved by projecting the observed signal onto a given subspace. Decentralized approaches avoid the need for performing such an operation at a central processor, thereby reducing congestion and increasing the robustness and the scalability of the network. Unfortunately, existing decentralized approaches either confine themselves to a reduced family of subspace projection tasks or need an infinite number of iterations to obtain the exact projection. To remedy these limitations, this paper develops a framework for computing a wide class of subspace projections in a decentralized fashion by relying on the notio…
Denoising of MR spectroscopy signals using total variation and iterative Gauss-Seidel gradient updates
2015
We present a fast variational approach for denoising signals from magnetic resonance spectroscopy (MRS). Differently from the TV approaches applied to denoising of images, this is the first time to our knowledge that it has been used for the processing of free induction decay signals from single-voxel spectroscopy (SVS) acquisitions. Another novelty in this study is the direct use of the Euler Lagrange formulation coupled with Gauss Seidel gradient updates to improve the speed of iteration and reduce ringing. Results from brain MRS signals show improvement in signal to noise ratio as well as reduction in estimation error in the quantification of metabolites.
Split Bregman Method for Gravitational Wave Denoising
2014
This paper presents a progress report in our aim to develop a Total Variation algorithm for denoising of gravitational waves. These algorithms, are routinely employed in the context of image processing and they do not need any a priori information on the signals. We apply our method to two different types of numerically-simulated gravitational wave signals, namely burst produced from the core collapse of rotating stars and waveforms from binary black hole mergers, and present a preliminary assessment of its capabilities.
3d mesh denoising using normal based myriad filter
2011
We propose a new filtering scheme for denoising of 3D objects which are represented by a triangular mesh. This scheme consists on applying myriad filter to face normals and then updating the vertices positions in order to preserve the original shape of the object. The choice of the Myriad is justified by the assumption of Cauchy distributed angles between surface normals. This filter improves the performance of a normal-based method which is adapted to the underlying mesh structure. To evaluate these methods of filtering, we use three error metrics. The first is based on the vertices, the second is based on the normals and the third is based on Hausdorff distance. Experimental results demon…
Modelling spatial and spectral systematic noise patterns on CHRIS/PROBA hyperspectral data
2006
In addition to typical random noise, remote sensing hyperspectral images are generally affected by non-periodic partially deterministic disturbance patterns due to the image formation process and characterized by a high degree of spatial and spectral coherence. This paper presents a new technique that faces the problem of removing the spatial coherent noise known as vertical stripping (VS) usually found in images acquired by push-broom sensors, in particular for the Compact High Resolution Imaging Spectrometer (CHRIS). The correction is based on the hypothesis that the vertical disturbance presents higher spatial frequencies than the surface radiance. The proposed method introduces a way to…
Correction of systematic spatial noise in push-broom hyperspectral sensors: application to CHRIS/PROBA images
2008
Hyperspectral remote sensing images are affected by different types of noise. In addition to typical random noise, nonperiodic partially deterministic disturbance patterns generally appear in the data. These patterns, which are intrinsic to the image formation process, are characterized by a high degree of spatial and spectral coherence. We present a new technique that faces the problem of removing the spatially coherent noise known as vertical striping, usually found in images acquired by push-broom sensors. The developed methodology is tested on data acquired by the Compact High Resolution Imaging Spectrometer (CHRIS) onboard the Project for On-board Autonomy (PROBA) orbital platform, whi…
Diffusion equations with negentropy applied to denoise mammographic images.
2006
Mammography is a radiographic technique used for the detection of breast lesions. The analysis of the digital image normally requires a previous application of filters as a preprocessing step to reduce the noise level of the image, while preserving important details to carry out a suitable diagnostic. In the literature, there are a large amount of denoising techniques applied to different medical images. In this work we have studied the performance of a diffusive filter with a stopping condition based on the statistical concept of negentropy, applied to denoise mammographic images. The negentropy has been succesfully prove with other denoising methods as independent component analysis by th…
Reducing Patient Radiation Dose With Image Noise Reduction Technology in Transcatheter Aortic Valve Procedures
2015
X-ray radiation exposure is of great concern for patients undergoing structural heart interventions. In addition, a larger group of medical staff is required and exposed to radiation compared with percutaneous coronary interventions. This study aimed at quantifying radiation dose reduction with implementation of specific image noise reduction technology (NRT) in transcatheter aortic valve implantation (TAVI) procedures. We retrospectively analyzed 104 consecutive patients with TAVI procedures, 52 patients before and 52 after optimization of x-ray radiation chain, and implementation of NRT. Patients with 1-step TAVI and complex coronary intervention, or complex TAVI procedures, were excluded…
Experimental analysis of acoustical properties of irregular cavities using laser refracto-vibrometry
2018
International audience; In this paper, the Scanning Laser Doppler Vibrometer (SLDV) is used to measure acoustic pressure in small regions of cavities for the study of acoustical localization. It is shown that this optical method leads to interesting information on localized acoustical modes inside irregular cavities, which are very difficult to observe using conventional microphone measurements. Indeed, localization regions are often of comparable size or even smaller than a typical microphone which can make this type of sensor intrusive. The SLDV is used to measure sound pressure after deriving the refracto-vibrometry method from its standard use. Data are obtained in a large area with a h…