K-SVD Based Denoising Algorithm for DoFP Polarization Image Sensors

This paper presents a novel K times singular value decomposition (K-SVD) based denoising algorithm for the division-of-focal-plane (DoFP) polarization image sensors. In the proposed implementation, the input DoFP image can be expressed by the optimum sparse combination of the dictionary elements via K-SVD and orthogonal matching pursuit (OMP) algorithms. As a result, this implementation is capable of eliminating the Gaussian noise significantly and well-preserving the details and edges of the target DoFP image. Our extensive experimental results on various test images show that the proposed algorithm yields better visual quality and maintains a lower PSNR value while compared with a wide range of previous implementations.

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