scholarly journals Spatial resolution, signal-to-noise and information capacity of linear imaging systems

2016 ◽  
Vol 24 (15) ◽  
pp. 17168 ◽  
Author(s):  
Timur Gureyev ◽  
Yakov Nesterets ◽  
Frank de Hoog
Keyword(s):  
Spatial Resolution ◽  
Imaging Systems ◽  
Information Capacity ◽  
Signal To Noise

scholarly journals Signal-to-noise, spatial resolution and information capacity of coherent diffraction imaging

IUCrJ ◽  
2018 ◽  
Vol 5 (6) ◽  
pp. 716-726 ◽  
Author(s):  
Timur E. Gureyev ◽  
Alexander Kozlov ◽  
Yakov I. Nesterets ◽  
David M. Paganin ◽  
Andrew V. Martin ◽  
...  
Keyword(s):  
Radiation Dose ◽  
Electron Density ◽  
Spatial Resolution ◽  
Three Dimensional ◽  
Information Capacity ◽  
Fourth Power ◽  
Imaging Method ◽  
Signal To Noise ◽  
Diffractive Imaging ◽  
Reconstructed Volume

It is shown that the average signal-to-noise ratio (SNR) in the three-dimensional electron-density distribution of a sample reconstructed by coherent diffractive imaging cannot exceed twice the square root of the ratio of the mean total number of scattered photons detected during the scan and the number of spatially resolved voxels in the reconstructed volume. This result leads to an upper bound on Shannon's information capacity of this imaging method by specifying the maximum number of distinguishable density distributions within the reconstructed volume when the radiation dose delivered to the sample and the spatial resolution are both fixed. If the spatially averaged SNR in the reconstructed electron density is fixed instead, the radiation dose is shown to be proportional to the third or fourth power of the spatial resolution, depending on the sampling of the three-dimensional diffraction space and the scattering power of the sample.

Information capacity and bandwidth limitations in the SEM

1989 ◽  
Vol 47 ◽  
pp. 84-85
Author(s):  
D. C. Joy ◽  
R. D. Bunn
Keyword(s):  
Signal To Noise Ratio ◽  
Critical Dimension ◽  
Information Capacity ◽  
Acquisition Time ◽  
Signal To Noise ◽  
Sem Image ◽  
Probe Size ◽  
Minimum Number ◽  
Noise Ratio ◽  
Signal Channel

The information available from an SEM image is limited both by the inherent signal to noise ratio that characterizes the image and as a result of the transformations that it may undergo as it is passed through the amplifying circuits of the instrument. In applications such as Critical Dimension Metrology it is necessary to be able to quantify these limitations in order to be able to assess the likely precision of any measurement made with the microscope.The information capacity of an SEM signal, defined as the minimum number of bits needed to encode the output signal, depends on the signal to noise ratio of the image - which in turn depends on the probe size and source brightness and acquisition time per pixel - and on the efficiency of the specimen in producing the signal that is being observed. A detailed analysis of the secondary electron case shows that the information capacity C (bits/pixel) of the SEM signal channel could be written as :

An autofocusing method for imaging the targets for TWI radar systems with correction of thickness and dielectric constant of wall

2018 ◽  
Vol 11 (1) ◽  
pp. 15-21 ◽  
Author(s):  
Sandeep Kaushal ◽  
Bambam Kumar ◽  
Dharmendra Singh
Keyword(s):  
Genetic Algorithm ◽  
Dielectric Constant ◽  
Continuous Wave ◽  
Signal To Noise Ratio ◽  
Imaging Systems ◽  
Signal To Noise ◽  
Radar Systems ◽  
Stepped Frequency ◽  
Correct Image ◽  
Wall Imaging

AbstractIn through the wall imaging systems, wall parameters like its thickness and dielectric constant play an important role in the true and correct image formation of an object behind the wall made of various materials like brick cement, wood, plastic, etc. Incorrect estimation of these parameters leads to dislocation of the object and smearing or blurriness of the image too. A new autofocusing technique for a stepped frequency continuous wave -based radar at the frequency of 1–3 Ghz has been developed that corrects the wall's parameters like its thickness and dielectric constant and provides a better focused image of the target. For this purpose, a peak signal to noise ratio -based autofocusing technique has been developed by using curve fitting and the genetic algorithm. It is observed that the proposed technique has capability to focus the image up to good extent.

scholarly journals Assessment of the Impacts of Image Signal-to-Noise Ratios in Impervious Surface Mapping

2019 ◽  
Vol 11 (22) ◽  
pp. 2603
Author(s):  
George Xian ◽  
Hua Shi ◽  
Cody Anderson ◽  
Zhuoting Wu
Keyword(s):  
Spatial Resolution ◽  
Signal To Noise Ratio ◽  
Spatial Scales ◽  
Regression Tree ◽  
Remote Sensing Data ◽  
Impervious Surface ◽  
Landsat 8 ◽  
Signal To Noise ◽  
Study Results ◽  
The Impact

Medium spatial resolution satellite images are frequently used to characterize thematic land cover and a continuous field at both regional and global scales. However, high spatial resolution remote sensing data can provide details in landscape structures, especially in the urban environment. With upgrades to spatial resolution and spectral coverage for many satellite sensors, the impact of the signal-to-noise ratio (SNR) in characterizing a landscape with highly heterogeneous features at the sub-pixel level is still uncertain. This study used WorldView-3 (WV3) images as a basis to evaluate the impacts of SNR on mapping a fractional developed impervious surface area (ISA). The point spread function (PSF) from the Landsat 8 Operational Land Imager (OLI) was used to resample the WV3 images to three different resolutions: 10 m, 20 m, and 30 m. Noise was then added to the resampled WV3 images to simulate different fractional levels of OLI SNRs. Furthermore, regression tree algorithms were incorporated into these images to estimate the ISA at different spatial scales. The study results showed that the total areal estimate could be improved by about 1% and 0.4% at 10-m spatial resolutions in our two study areas when the SNR changes from half to twice that of the Landsat OLI SNR level. Such improvement is more obvious in the high imperviousness ranges. The root-mean-square-error of ISA estimates using images that have twice and two-thirds the SNRs of OLI varied consistently from high to low when spatial resolutions changed from 10 m to 20 m. The increase of SNR, however, did not improve the overall performance of ISA estimates at 30 m.

scholarly journals Enhancement of spatial resolution of terahertz imaging systems based on terajet generation by dielectric cube

APL Photonics ◽  
2017 ◽  
Vol 2 (5) ◽  
pp. 056106 ◽  
Author(s):  
Hai Huy Nguyen Pham ◽  
Shintaro Hisatake ◽  
Oleg Vladilenovich Minin ◽  
Tadao Nagatsuma ◽  
Igor Vladilenovich Minin
Keyword(s):  
Spatial Resolution ◽  
Terahertz Imaging ◽  
Imaging Systems

Spatial resolution and signal-to-noise ratio in x-ray imaging

2019 ◽  
Author(s):  
Timur Gureyev ◽  
David M. Paganin ◽  
Alex Kozlov ◽  
Harry Quiney
Keyword(s):  
Spatial Resolution ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
X Ray ◽  
X Ray Imaging ◽  
Noise Ratio

k-Space filtering in 2D gradient-echo breath-hold hyperpolarized3He MRI: Spatial resolution and signal-to-noise ratio considerations

2002 ◽  
Vol 47 (4) ◽  
pp. 687-695 ◽  
Author(s):  
Jim M. Wild ◽  
Martyn N.J. Paley ◽  
Magalie Viallon ◽  
Wolfgang G. Schreiber ◽  
Edwin J.R. van Beek ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Signal To Noise Ratio ◽  
Breath Hold ◽  
Gradient Echo ◽  
Signal To Noise ◽  
Noise Ratio
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