scholarly journals On-Orbit Signal-to-Noise Ratio Test Method for Night-Light Camera in Luojia 1-01 Satellite Based on Time-Sequence Imagery

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4077 ◽  
Author(s):  
Wang ◽  
Zhong ◽  
Su
Keyword(s):  
Remote Sensing ◽  
Signal To Noise Ratio ◽  
Time Sequence ◽  
Focal Plane Arrays ◽  
Test Method ◽  
Light Illumination ◽  
Ratio Test ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Theoretical Results

Night-light remote sensing imaging technologies have increasingly attracted attention with the development and application of focal plane arrays. On-orbit signal-to-noise ratio (SNR) test is an important link to evaluate night-light camera’s radiometric performance and the premise for quantitative application of remote sensing imageries. Under night-light illumination conditions, the illuminance of ground objects is very low and varies dramatically, the spatial uniformity of each pixel’s output cannot be guaranteed, and thus the traditional on-orbit test methods represented by variance method are unsuitable for low-resolution night-light cameras. To solve this problem, we proposed an effective on-orbit SNR test method based on consecutive time-sequence images that including the same objects. We analyzed the radiative transfer process between night-light camera and objects, and established a theoretical SNR model based on analysis of the generation and main sources of signal electrons and noise electrons. Finally, we took Luojia 1-01 satellite, the world’s first professional night-light remote sensing satellite, as reference and calculated the theoretical SNR and actual on-orbit SNR using consecutive images captured by Luojia 1-01 satellite. The actual results show the similar characteristics as theoretical results, and are higher than the theoretical results within the reasonable error tolerance, which fully guarantee the detection ability of night-light camera and verify the validity of this time-sequence-based method.

Noise Performance and Signal-to-Noise Ratio of Shear Strain Elastograms

2005 ◽  
Vol 27 (3) ◽  
pp. 145-165 ◽  
Author(s):  
Arun Thitai Kumar ◽  
Jonathan Ophir ◽  
Thomas A. Krouskop
Keyword(s):  
Shear Strain ◽  
Signal To Noise Ratio ◽  
Axial Strain ◽  
Center Frequency ◽  
Theoretical Expression ◽  
Lateral Strain ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Theoretical Results ◽  
Phantom Experiments

In this paper, we develop a theoretical expression for the signal-to-noise ratio (SNR) of shear strain elastograms. The previously-developed ideas for the axial strain filter (ASF) and lateral strain filter (LSF) are extended to define the concept of the shear strain filter (SSF). Some of our theoretical results are verified using simulations and phantom experiments. The results indicate that the signal-to-noise ratio of shear-strain elastograms ( SNRsse) improves with increasing shear strain and with improvements in system parameters such as the sonographic signal-to-noise ratio ( SNRs) beamwidth, center frequency and fractional bandwidth. The results also indicate that the amount of axial strain present along with the shear strain is an important parameter that determines the upper bound on SNRsse. The SNRsse will be higher in the absence of additional deformation due to axial strain.

Error Analysis for Estimation of Trace Vapor Concentration Pathlength in Stack Plumes

2003 ◽  
Vol 57 (6) ◽  
pp. 614-621 ◽  
Author(s):  
Neal B. Gallagher ◽  
Barry M. Wise ◽  
David M. Sheen
Keyword(s):  
Remote Sensing ◽  
Error Analysis ◽  
Near Infrared ◽  
Signal To Noise Ratio ◽  
Chemical Vapor ◽  
Noise Model ◽  
Vapor Concentration ◽  
Signal To Noise ◽  
Sensing Applications ◽  
Noise Ratio

Near-infrared hyperspectral imaging is finding utility in remote sensing applications such as detection and quantification of chemical vapor effluents in stack plumes. Optimizing the sensing system or quantification algorithms is difficult because reference images are rarely well characterized. The present work uses a radiance model for a down-looking scene and a detailed noise model for dispersive and Fourier transform spectrometers to generate well-characterized synthetic data. These data were used with a classical least-squares-based estimator in an error analysis to obtain estimates of different sources of concentration-pathlength quantification error in the remote sensing problem. Contributions to the overall quantification error were the sum of individual error terms related to estimating the background, atmospheric corrections, plume temperature, and instrument signal-to-noise ratio. It was found that the quantification error depended strongly on errors in the background estimate and second-most on instrument signal-to-noise ratio. Decreases in net analyte signal (e.g., due to low analyte absorbance or increasing the number of analytes in the plume) led to increases in the quantification error as expected. These observations have implications on instrument design and strategies for quantification. The outlined approach could be used to estimate detection limits or perform variable selection for given sensing problems.

SCIMP—A scanning interferometric multiplex photometer

1978 ◽  
Vol 56 (6) ◽  
pp. 681-686 ◽  
Author(s):  
G. G. Shepherd ◽  
A. J. Deans ◽  
Y. P. Neo
Keyword(s):  
Remote Sensing ◽  
Comparative Analysis ◽  
Signal To Noise Ratio ◽  
Interference Filter ◽  
Wavelength Shift ◽  
Spectral Elements ◽  
Signal To Noise ◽  
Airborne Remote Sensing ◽  
Noise Ratio ◽  
Rocket Measurements

An interference filter photometer concept is described in which equally-spaced spectral elements of equal width are generated. The method takes advantage of the wavelength shift of off-axis radiation transmitted by the filter, and is accomplished by the use of masks in the location of the field stop. This technique lends itself to multiplexing, using Fourier or Hadamard coding, but a direct spectral configuration is also possible. The advantages of the concept and a comparative analysis of signal-to-noise ratio are described. The technique has been employed in ground based airglow studies, airborne remote sensing, and rocket measurements of airglow and aurora.

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