Post-experimental denoising and background subtraction of surface plasmon resonance images for better quantification
A method was proposed to improve the quality of noise- and/or uneven background-degraded images obtained by surface plasmon resonance imaging experiments. The noise was suppressed by adaptive median filter in combination with wavelet transform, while the uneven background was flattened by subtraction with a three-dimensionally fitted surface. These operations improved the signal-to-noise ratio from 23.83 dB to 41.36 dB for real images and widened the quantitative linear range of picture gray value vs. concentration for about one order of magnitude, with linear correlation coefficient increased from 0.9558 to 0.9982. The method can be performed repeatedly until a better result is obtained and is thus cost-effective, highly competitive to experimental strategies and other computational methods. (C) 2012 Elsevier B.V. All rights reserved,
background subtraction surface plasmon resonance imaging adaptive median filter wavelet transform least square surface fitting quantitative analysis