COMPARATIVE ANALYSIS OF POTATO DISEASE LEAF IMAGE DENOISING METHODS BASED ON MATLAB
DOI:
https://doi.org/10.47390/ts-v3i10y2025No6Ключевые слова:
image denoising; Gaussian filtering; Mean filtering; Median filtering; Bilateral filtering; Wavelet filtering.Аннотация
Image denoising is one of the indispensable operations in image preprocessing, and the purpose of denoising is to effectively inhibit the excess noise components in the screen under the premise of ensuring that the original effective information of the image remains unchanged. In order to study the advantages and disadvantages of various denoising algorithms, this paper theoretically analyses Gaussian filtering, Mean filtering, Median filtering, Bilateral filtering and Wavelet filtering, and uses MATLAB to carry out simulation implementation and comparative analysis of various filtering and denoising effects on potato diseased leaf images.
Библиографические ссылки
1. BERTALMIO M.Denoising of photographic images and video: fundamentals, open challenges and new trends[M].Barcelona, spain: springer, 2018.
2. Sanaa A, Kruglova L V. Basic mathematical models for pattern recognition and image quality improvement[J]. Current Research, 2025 (18 (253)): 7-15.
3. Sun, M. (2013). Fundamentals of Digital Image Processing and Analysis: Implementation with MATLAB and VC++. Beijing: Publishing House of Electronics Industry.
4. Guan, X. P., Zhao, L. X., & Tang, Y. G. (2005). Hybrid filtering methods for image denoising. Journal of Image and Graphics, (3), 332-337.
5. KO S J, LEE Y H. Center weighted median filters and their applications to image enhancement[J]. IEEE transactions on circuits and systems,1991,38(9): 984-993.
6. MALLAT S G,Multifrequency channel decompositions of images and wavelet models[J]. IEEE transactions on acoustics, speech, and signal processing, 1989, 3 7(12): 2091-2110.
7. WANG Z, BOVIK A C, SHEIKH H R, et al. Image quality assessment: From error visibility to structural similarity[J].IEEE transactions on image processing, 2004,13(4): 600-612.
8. WANG Z, BOVIK A C. Mean squared error: Love it or leave it? A new look at signal fidelity measures[J]. IEEE signal processing magazine,2009,26(1): 98-117.


