An Improved Adaptive Weighted Mean Filtering Approach for Metallographic Image Processing

Abstract

Abstract Background As noise brings great error in the analysis of metallographic images, an adaptive weighted mean filtering method proposed to overcome the shortcomings of the standard mean filtering method. Methods The method used to detect the pulse noise points in the image, and then the modified mean method used to filter out the detected noise points. Patents on metallographic image processing have discussed for the development of the proposed methodology. Results It is shown that filter window can be filtered in comparison with the conventional 3×3, 5×5 and 7×7 filt window to reduce noise detection and reduce the complexity of the weight calculation. Conclusion It can be concluded that this method can better protect the details of the image, has better filtering effect than the standard mean filtering, and its processing speed is faster than the median filtering of the large window, which has profound significance for the edge detection and processing of the metallographic image.