@inproceedings{4bd1b754cfdb44bfaea768d8f11c6bff,
title = "Performance Evaluation of Gaussian Noise Denoising Algorithms for DoFP Polarization Image Sensors",
abstract = "This paper compares the performance of the reported denoising algorithms for Division-of-Focal-Plane (DoFP) polarization image sensors. While the reported denoising algorithms each covered analysis on interpolated images in their respective publications, analysis was not extended to less sightseen parameters, namely Fully Polarized and Unpolarized images, which are other derivatives from Stokes parameters. In this paper, we focus our analysis and comparison on these images as they provide more details than Degree of Linear Polarization (DoLP). We use a Building test image to compare visually as well as analytically in terms of Peak-Signal-to-Noise-Ratio (PSNR) and Structural Similarity (SSIM) Index. Both Comparison results show the Block Matching and 3D (BM3D) filtering method ranking highest followed by the K-Times Singular Value Decomposition (K-SVD) method as a close second.",
keywords = "Polarization image, division of focal plane, image denoising",
author = "Abubakar Abubakar and Maen Takruri and \{Al Naqbi\}, Noora and \{Al Shehhi\}, Hessa and Hutair, \{Wafaa Ba\} and Amine Bermak",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2019 ; Conference date: 19-11-2019 Through 21-11-2019",
year = "2019",
month = nov,
doi = "10.1109/ICECTA48151.2019.8959603",
language = "English",
series = "2019 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2019 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2019",
address = "United States",
}