An Efficient Image Denoising Approach for Higher Noise Levels Using Non-Linear Filters in Yarn Images
In order to improve the prediction accuracy of yarn quality efficient noise reduction algorithms with lesser complexity are an essential. Hence the most efficient algorithm for noise reduction must be chosen in such a way that the cost for noise removal is a less as possible, but a large portion of noise is removed. The common method for the removal of noise is optimal linear filtering method, and some algorithms in this method are Weighted Median, Center Weighted Median, and Adaptive Median.In the test of real data, it shows that the algorithm has a good effect, improves the prediction process of yarn quality. The Improved Wiener filter algorithm can be adjusted depending on the characteristics of noise signal too. After each of the techniques are applied to the samples, PSNR, SNR, MSE and SSIM are calculated. All of the above techniques show thatImproved Wiener filter method gives better results after pre-processing, as seen in the performance metrics results.