Spatial resolution of imaging with diffusing light: Edge spread function measurements on a realistic tissue phantom

1999 ◽  
Vol 26 (3) ◽  
pp. 462-471 ◽  
Author(s):  
Rinaldo Cubeddu ◽  
Antonio Pifferi ◽  
Paola Taroni ◽  
Alessandro Torricelli ◽  
Gianluca Valentini
Keyword(s):  
Spatial Resolution ◽  
Tissue Phantom ◽  
Spread Function ◽  
Resolution Of Imaging

Spatial resolution of imaging plate with flash X-rays and its utilization for radiography

2015 ◽  
Author(s):  
A. M. Shaikh ◽  
Romesh C. ◽  
T. S. Kolage ◽  
Archana Sharma
Keyword(s):  
Spatial Resolution ◽  
Imaging Plate ◽  
X Rays ◽  
Resolution Of Imaging

Atmospheric scattering effect on spatial resolution of imaging systems

1997 ◽  
Vol 14 (6) ◽  
pp. 1329 ◽  
Author(s):  
B. Ben Dor ◽  
A. D. Devir ◽  
G. Shaviv ◽  
P. Bruscaglioni ◽  
P. Donelli ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Imaging Systems ◽  
Atmospheric Scattering ◽  
Scattering Effect ◽  
Resolution Of Imaging

scholarly journals Blind Fusion of Hyperspectral Multispectral Images Based on Matrix Factorization

2021 ◽  
Vol 13 (21) ◽  
pp. 4219
Author(s):  
Jian Long ◽  
Yuanxi Peng
Keyword(s):  
Response Function ◽  
Spatial Resolution ◽  
Point Spread Function ◽  
Spectral Response ◽  
Estimation Method ◽  
Hyperspectral Images ◽  
Fusion Method ◽  
Multispectral Images ◽  
Point Spread ◽  
Spread Function

The fusion of low spatial resolution hyperspectral images and high spatial resolution multispectral images in the same scenario is important for the super-resolution of hyperspectral images. The spectral response function (SRF) and the point spread function (PSF) are two crucial prior pieces of information in fusion, and most of the current algorithms need to provide these two preliminary pieces of information in advance, even for semi-blind fusion algorithms at least the SRF. This causes limitations in the application of fusion algorithms. This paper aims to solve the dependence of the fusion method on the point spread function and proposes a method to estimate the spectral response function from the images involved in the fusion to achieve blind fusion. We conducted experiments on simulated datasets Pavia University, CAVE, and the remote sensing images acquired by two spectral cameras, Sentinel 2 and Hyperion. The experimental results show that our proposed SRF estimation method can improve the PSNR value by 5 dB on average compared with other state-of-the-art SRF estimation results. The proposed blind fusion method can improve the PSNR value of fusion results by 3–15 dB compared with other blind fusion methods.

Atmospheric scattering effect on spatial resolution of imaging systems: theory

1997 ◽  
Author(s):  
Baruch Ben-Dor ◽  
Adam D. Devir ◽  
Gal Shaviv ◽  
Piero Bruscaglioni ◽  
P. Donelli ◽  
...  
Keyword(s):  
Systems Theory ◽  
Spatial Resolution ◽  
Imaging Systems ◽  
Atmospheric Scattering ◽  
Scattering Effect ◽  
Resolution Of Imaging

Imaging the Solar Corona during the 2015 March 20 Eclipse using LOFAR

2020 ◽  
Author(s):  
Aoife Maria Ryan ◽  
Peter T. Gallagher ◽  
Eoin P. Carley ◽  
Diana E. Morosan ◽  
Michiel A. Brentjens ◽  
...  
Keyword(s):  
Solar Corona ◽  
Spatial Resolution ◽  
Electromagnetic Waves ◽  
High Spatial Resolution ◽  
Low Frequency ◽  
Angular Width ◽  
Interferometric Imaging ◽  
Low Frequencies ◽  
Point Spread ◽  
Spread Function

<p>The solar corona is a highly-structured plasma which reaches temperatures of more than ~2MK. At low radio frequencies (≤ 400 MHz), scattering and refraction of electromagnetic waves are thought to broaden sources to several arcminutes. However, exactly how source size relates to scattering due to turbulence is still subject to investigation. This is mainly due to the lack of high spatial resolution observations of the solar corona at low frequencies. Here, we use the LOw Frequency ARray (LOFAR) to observe the solar corona at 120-180 MHz using baselines of up to ~3.5 km (~1--2’) during a partial solar eclipse of 2015 March 20. We use a lunar de-occultation technique to achieve higher spatial resolution than that attainable via traditional interferometric imaging. This provides a means of studying source sizes in the corona that are smaller than the angular width of the interferometric point spread function. </p>

scholarly journals Retinal Image Denoising via Bilateral Filter with a Spatial Kernel of Optimally Oriented Line Spread Function

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Yunlong He ◽  
Yuanjie Zheng ◽  
Yanna Zhao ◽  
Yanju Ren ◽  
Jian Lian ◽  
...  
Keyword(s):  
Image Denoising ◽  
Retinal Image ◽  
Bilateral Filter ◽  
Retinal Vessels ◽  
Line Spread Function ◽  
Spread Function ◽  
Vessel Structure ◽  
Local Window ◽  
Resolution Of Imaging ◽  
Line Spread

Filtering belongs to the most fundamental operations of retinal image processing and for which the value of the filtered image at a given location is a function of the values in a local window centered at this location. However, preserving thin retinal vessels during the filtering process is challenging due to vessels’ small area and weak contrast compared to background, caused by the limited resolution of imaging and less blood flow in the vessel. In this paper, we present a novel retinal image denoising approach which is able to preserve the details of retinal vessels while effectively eliminating image noise. Specifically, our approach is carried out by determining an optimal spatial kernel for the bilateral filter, which is represented by a line spread function with an orientation and scale adjusted adaptively to the local vessel structure. Moreover, this approach can also be served as a preprocessing tool for improving the accuracy of the vessel detection technique. Experimental results show the superiority of our approach over state-of-the-art image denoising techniques such as the bilateral filter.

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