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A family of efficient nonlinear filters for video restoration

Abbas J., Domański M.

Machine Graphics and Vision

2000

Vol. 9, No. 1/2

353-361

The paper deals with denoising of color video sequences using median-based filters. The filters emply a simple structure with nonlinear predictor and prediction error processed by a static (memoryless) noninear element. The basic idea is to predict a pixel value by using a nonlinear filter, and then to compare this value to that in the input (Corrupted) image. Usually these two values are different and a decision has to be made about the pixel value at the filter output. This value can be considered as a sum of the prediction errors are set to zero because they are can be classifield as caused by impulsive noise samples. Soft decisions on classification of prediction errors lead to good results for test images. The filters are very suitable for impulsive noise removal from color images. Preservation of textures and fine details are adventages of the filters proposed. The experimental data prove that these filters outperform classic nonlinear median-based filters like vector median, recursive median and weighted median. In the paper, it is proven that application of prediction error processing results in improved efficiency of video restoration.