Mean square error performance evaluation of a commercial speckle imaging system using simulated imagery

2014 ◽  
Author(s):  
Jeremy P. Bos ◽  
Aaron Paolini ◽  
Eric J. Kelmelis ◽  
Michael C. Roggemann
Keyword(s):  
Performance Evaluation ◽  
Mean Square Error ◽  
Imaging System ◽  
Mean Square ◽  
Error Performance ◽  
Speckle Imaging ◽  
Mean Square Error Performance

Joint demosaicing of colour and polarisation from filter arrays

2021 ◽  
Vol 2021 (29) ◽  
pp. 288-293
Author(s):  
Alexandra Spote ◽  
Pierre-Jean Lapray ◽  
Jean-Baptiste Thomas ◽  
Ivar Farup
Keyword(s):  
Mean Square Error ◽  
Imaging System ◽  
Signal To Noise Ratio ◽  
Minimum Mean Square Error ◽  
Mean Square ◽  
Interpolation Algorithm ◽  
Signal To Noise ◽  
Image Content ◽  
Filter Array ◽  
Array Imaging

This article considers the joint demosaicing of colour and polarisation image content captured with a Colour and Polarisation Filter Array imaging system. The Linear Minimum Mean Square Error algorithm is applied to this case, and its performance is compared to the state-of-theart Edge-Aware Residual Interpolation algorithm. Results show that the LMMSE demosaicing method gives statistically higher scores on the largest tested database, in term of peak signal-to-noise ratio relatively to a CPFA-dedicated algorithm.

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