Abstract
This paper investigates the performance of digital correlated double sampling (DCDS) for processing of image sensor signals in the presence of white and 1/f noise. The DCDS is compared with the dual slope integrator, which is the optimal analogue processing technique when only white noise is present. Based on the concept of matched filters, the paper derives and explores the optimal signal processing algorithms for signals with dominant 1/f noise, resulting in the highest achievable signal-to-noise ratio (SNR). Experimental results based on optimal DCDS on artificially generated 1/f noise signals are presented and discussed, together with the limitations of the method for more realistic sensor signals. It is shown that the noise level of the optimal DCDS can get close to the theoretical minimum.
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