A Comparison Study for the Effect of Applying Image Filters on Image’s Statistical Distribution
Image filters has taken attention last few years due to its importance in terms of image processing and applications. Applying image filters on images elements can be affected by the values of image parameters, which resulted from any processing tasks. By applying image filters, we can extent the image processing methods to present higher productivity. In this paper, we compare the effect of applying five image filters on the statistical distribution, which are (Laplacian, Differentiation, LOG, Sharpening, and Gaussian). Our method has been applied for a number of textural images (water texture, wool texture, and wood texture), the images has been divided for three groups according to the texture type. The result of our method proved that some of image filter affects the statistical distribution of image elements which are: (Differentiation, LOG, Sharpening) while other do not affect the parameter distribution (Laplacian, Gaussian). We evaluate our method by calculating the value of (MSE). The method opens the door in front of extending such technique with other image processing aspects. Keywords: Images processing, Image filtering, Statistical distribution, Textural Images, Probability Density Function
REFERENCES:  Chen, C.-h. (2015). Handbook of pattern recognition and computer vision: World Scientific.  Christe, S. A., Vignesh, M., & Kandaswamy, A. (2012). An efficient FPGA implementation of MRI image filtering and tumor characterization using Xilinx system generator. arXiv preprint arXiv:1201.2542.  Du, C.-J., & Sun, D.-W. (2004). Recent developments in the applications of image processing techniques for food quality evaluation. Trends in food science & technology, 15(5), 230-249.  He, K., Sun, J., & Tang, X. (2013). Guided image filtering. IEEE transactions on pattern analysis and machine intelligence, 35(6), 1397-1409.  Hogg, R. V., & Craig, A. T. (1995). Introduction to mathematical statistics.(5"" edition): Upper Saddle River, New Jersey: Prentice Hall.  Li, Z., Zheng, J., Zhu, Z., Yao, W., & Wu, S. (2015). Weighted guided image filtering. IEEE Transactions on Image Processing, 24(1), 120-129.  Matthews, J. (2016). Medical image processing: Google Patents.  Milanfar, P. (2013). A tour of modern image filtering: New insights and methods, both practical and theoretical. IEEE Signal Processing Magazine, 30(1), 106-128.  Mittal, A., & Dubey, S. K. (2013). Analysis of MRI images of rheumatoid arthritis through morphological image processing techniques. IJCS, 10(2-3), 118-122.  Nishikawa, T., Yoshida, J., Sugiyama, T., & Fujino, Y. (2012). Concrete crack detection by multiple sequential image filtering. Computer Ǧ Aided Civil and Infrastructure Engineering, 27(1), 29-47.  Pitas, I. (2000). Digital image processing algorithms and applications: John Wiley & Sons.  Rani, V. (2013). A brief study of various noise model and filtering techniques. Journal of global research in computer science, 4(4), 166-171.  Satorra, A., & Bentler, P. M. (2001). A scaled difference chi-square test statistic for moment structure analysis. Psychometrika, 66(4), 507-514.  Semmlow, J. L., & Griffel, B. (2014). Biosignal and medical image processing: CRC press.  Shrivakshan, G., & Chandrasekar, C. (2012). A comparison of various edge detection techniques used in image processing. IJCSI International Journal of Computer Science Issues, 9(5), 272-276.  Wood, S. N. (2011). Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 73(1), 3-36.
Copyright (c) 2022 Journal of Education for Pure Science- University of Thi-Qar
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to Journal of education for Pure Science (Jeds), University of Thi-Qar as publisher of the journal.
Copyright encompasses exclusive rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms and any other similar reproductions, as well as translations. The reproduction of any part of this journal, its storage in databases and its transmission by any form or media, such as electronic, electrostatic and mechanical copies, photocopies, recordings, magnetic media, etc. , will be allowed only with a written permission from Journal of education for Pure Science (Jeds), University of Thi-Qar.
Journal of education for Pure Science (Jeds), University of Thi-Qar, the Editors and the Advisory International Editorial Board make every effort to ensure that no wrong or misleading data, opinions or statements be published in the journal. In any way, the contents of the articles and advertisements published in the Journal of education for Pure Science (Jeds), University of Thi-Qar are sole and exclusive responsibility of their respective authors and advertisers.