Abstract
In this paper, we present four denoising algorithms dedicated to the division of focal plane (DoFP) polarization image sensors, including the average filtering, median filtering, Wiener filtering and wavelet threshold denoising algorithms. Compared with the previous implementations solely based on the Gaussian noise model, this paper, for the first time, covers the non-Gaussian noises, such as the salt & pepper noise and Poisson noise. According to our extensive experimental results, the wavelet threshold denoising outperforms for suppressing the Gaussian noise; while the median filtering and the Wiener filtering outperform for suppressing the low-density salt & pepper noise and Poisson noise, respectively.
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