Abstract
A content-based nonlinear filter capable of eliminating impulsively modeled artifacts from images and videos is proposed. The algorithm is a nonlinear filter that chooses median of the array or modified trimmed winsorized median of the array as the threshold to estimate the pixel is noisy or not. The median or modified winsorized median will act as a measure of central tendency to estimate the pixel is noisy or not. There are two demarcation levels used to conclude the estimated pixel is noisy or not. The first demarcation is named ad TH1 which holds value between (20 and 35). The second demarcation level is called TH2 which holds value between (0 and 15). The first delimiter says that the processed pixel is noisy or not and the second delimiter says that the median of the array is faulty or not. The proposed algorithm is applied on different defaced images and found to give very good visual results.
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Kameswari, D.V.N., Divya, M., Vasanth, K., Pradeep Kumar Reddy, S., Nagaraj, S. (2022). Content-Based Nonlinear Filter for the Removal of Impulsively Modeled Artifacts from Images and Videos. In: Kumar Jain, P., Nath Singh, Y., Gollapalli, R.P., Singh, S.P. (eds) Advances in Signal Processing and Communication Engineering. Lecture Notes in Electrical Engineering, vol 929. Springer, Singapore. https://doi.org/10.1007/978-981-19-5550-1_7
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DOI: https://doi.org/10.1007/978-981-19-5550-1_7
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