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Transformation of image-signal-dependent noise into image-signal-independent noise
Optics Letters, 1981A point transformation, the normalizing transform, is presented, which, when applied to a measured noisy image, renders its noise signal independent. The transform is suitable for arbitary noise-to-signal dependence. We demonstrate its applicability and its limitations by using, as an example, noisy signals that belong to a family of gamma-distributed ...
P R, Prucnal, B E, Saleh
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Noise equalization within EIT images
Physiological Measurement, 1994We first describe experiments designed to measure the spatial distribution of noise within an electrical impedance tomographic image of a saline-filled tank. These experiments show that the noise increases by a factor of up to 30 from the periphery towards the centre of the image.
W, Wang +3 more
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Analysis of noise image and research for noise image identification
SPIE Proceedings, 2007In this paper, we propose a new Non-marking algorithm to calculate the Multi-degree connectivity in Binary Images with noise. In this method we first divide the Image into several grids, by marking the color of the grids. We can filter out the noise from the Image. When scanning the Image, we read the grids instead of pixels.
Yong Sun, Ye Zhao, Jing Wang, Daoqin Yu
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Noise Suppression in Coherent Imaging
Applied Optics, 1973Several noise suppression techniques in coherent imaging systems are described. For holographic imaging the diffuse wave, periodic phase modulation, and multiple wave techniques are compared and the implementation of the last is considered. For lens-type imaging systems the use of multiple incoherent waves results in excellent noise suppression.
J, Upatnieks, R W, Lewis
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Accurate Image Domain Noise Insertion in CT Images
IEEE Transactions on Medical Imaging, 2020Tools to simulate lower dose, noisy computed tomography (CT) images from existing data enable protocol optimization by quantifying the trade-off between patient dose and image quality. Many studies have developed and validated noise insertion techniques; however, most of these tools operate on proprietary projection data which can be difficult to ...
Sarah E. Divel, Norbert J. Pelc
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Color Image Noise Covariance Estimation with Cross-Channel Image Noise Modeling
2018 IEEE International Conference on Multimedia and Expo (ICME), 2018Noise estimation is crucial in many image processing tasks such as denoising. Most of the existing noise estimation methods are specially developed for grayscale images. For color images, these methods simply handle each color channel independently, without considering the correlation across channels.
Li Dong, Jiantao Zhou, Tao Dai
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Image noise-informative map for noise standard deviation estimation
2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011The problem of automatic detection of image areas that can be reliably selected for accurate estimation of additive noise standard deviation (STD), irrespectively to processed image properties, is considered in this paper. For getting accurate estimate of either texture or noise parameters involved, we distinguish two complementary image informative ...
Uss, Mikhail +4 more
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Image noise removal using image inpainting
SPIE Proceedings, 2012In this paper, new methods are addressed for impulse and speckle noise removal in images. The approach is based on the fusion of noise detection and image inpainting techniques. To avoid destroying the real structures of the image, the noise areas are first recognized to be repaired by an inpainting algorithm, subsequently. To distinguish the impulse
Somayeh Bakhtiari +3 more
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Image enhancement, image quality, and noise
SPIE Proceedings, 2005The Multiscale Retinex With Color Restoration (MSRCR) is a non-linear image enhancement algorithm that provides simultaneous dynamic range compression, color constancy and rendition. The overall impact is to brighten up areas of poor contrast/lightness but not at the expense of saturating areas of good contrast/brightness. The downside is that with the
Zia-ur Rahman +3 more
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Passive Imaging with Ambient Noise
2016Waves generated by opportunistic or ambient noise sources and recorded by passive sensor arrays can be used to image the medium through which they travel. Spectacular results have been obtained in seismic interferometry, which open up new perspectives in acoustics, electromagnetics, and optics.
Garnier, Josselin, Papanicolaou, G.
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