Measurement and analysis of perceivable signal-to-noise ratio for infrared imaging system with human vision

2012 ◽  
Author(s):  
Xin Liu ◽  
Jing Zhao ◽  
Honghua Chang ◽  
Lin Ma
Keyword(s):  
Infrared Imaging ◽  
Imaging System ◽  
Signal To Noise Ratio ◽  
Human Vision ◽  
Signal To Noise ◽  
Infrared Imaging System ◽  
Measurement And Analysis ◽  
Noise Ratio

Design of imaging system of cloud and aerosol polarization imager with high signal-to-noise ratio

2018 ◽  
Vol 47 (11) ◽  
pp. 1111006
Author(s):  
李 帅 Li Shuai ◽  
徐抒岩 Xu Shuyan ◽  
刘栋斌 Liu Dongbin ◽  
张 航 Zhang Hang
Keyword(s):  
Imaging System ◽  
Signal To Noise Ratio ◽  
High Signal ◽  
Signal To Noise ◽  
Noise Ratio

Improved signal to noise ratio and sensitivity of an infrared imaging video bolometer on large helical device by using an infrared periscope

2014 ◽  
Vol 85 (7) ◽  
pp. 073107 ◽  
Author(s):  
Shwetang N. Pandya ◽  
Byron J. Peterson ◽  
Kiyofumi Mukai ◽  
Ryuichi Sano ◽  
Akito Enokuchi ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Noise Ratio

scholarly journals Signal to Noise Ratio as a Cross-Platform Metric for Intraoperative Fluorescence Imaging

2020 ◽  
Vol 19 ◽  
pp. 153601212091369
Author(s):  
Asmaysinh Gharia ◽  
Efthymios P. Papageorgiou ◽  
Simeon Giverts ◽  
Catherine Park ◽  
Mekhail Anwar
Keyword(s):  
Tumor Cells ◽  
Imaging System ◽  
Signal To Noise Ratio ◽  
Size Variation ◽  
Pixel Size ◽  
Signal To Noise ◽  
Noise Sources ◽  
Noise Measurements ◽  
Noise Ratio ◽  
The Impact

Real-time molecular imaging to guide curative cancer surgeries is critical to ensure removal of all tumor cells; however, visualization of microscopic tumor foci remains challenging. Wide variation in both imager instrumentation and molecular labeling agents demands a common metric conveying the ability of a system to identify tumor cells. Microscopic disease, comprised of a small number of tumor cells, has a signal on par with the background, making the use of signal (or tumor) to background ratio inapplicable in this critical regime. Therefore, a metric that incorporates the ability to subtract out background, evaluating the signal itself relative to the sources of uncertainty, or noise is required. Here we introduce the signal to noise ratio (SNR) to characterize the ultimate sensitivity of an imaging system and optimize factors such as pixel size. Variation in the background (noise) is due to electronic sources, optical sources, and spatial sources (heterogeneity in tumor marker expression, fluorophore binding, and diffusion). Here, we investigate the impact of these noise sources and ways to limit its effect on SNR. We use empirical tumor and noise measurements to procedurally generate tumor images and run a Monte Carlo simulation of microscopic disease imaging to optimize parameters such as pixel size.

scholarly journals Least Significant Braille Method in Steganography Using Digital Image Media For Security Message

2017 ◽  
Vol 6 (1) ◽  
pp. 15-20
Author(s):  
Megah Mulya ◽  
Zikry Sugiwa
Keyword(s):  
Digital Image ◽  
Signal To Noise Ratio ◽  
Human Vision ◽  
Secret Message ◽  
Signal To Noise ◽  
Stego Image ◽  
Resistance Level ◽  
Noise Ratio

Confidentiality of the message or the information is the most important and essential.  It is very influential on the party who has the valuable message when they want to exchange messages on others.  To keep the message is not known to others, the necessary security on the message.  Steganography is one technique for providing security to the message.  Steganography is a technique to hide messages in a medium, such as pictures, sounds and video.  Steganographic technique used in this study is the Least Significant Braille (LSBraille).  This technique makes use of human vision in the message on the bit value was not significant.  This study focuses on how much resistance level stego image to various image processes and measure results accuracy Peak Signal to Noise Ratio (PSNR).  From the result of the insertion of a secret message, that the level of resistance stego image is not resistant to digital image processing.  The result of the calculation of PSNR value obtained from experiments on all data samples between 51-73 db.

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