Adaptive window-based filter for high-density impulse noise suppression

被引：0
作者：
Rani S. [1 ]
Chabbra Y. [2 ]
Malik K. [3 ]
机构：
[1] Department of Computer Science and Application, CT University, Punjab, Ludhiana
[2] Department of Electronics and Communication, CT University, Punjab, Ludhiana
[3] Department of Computer Science and Engineering, CT University, Punjab, Ludhiana
来源：
Measurement: Sensors | 2022年 / 24卷
关键词：
Adaptive filter; Denoise; Impulse noise; Restoration;
D O I：
10.1016/j.measen.2022.100455
中图分类号：
学科分类号：
摘要：
One of the primary factors that lower image quality is noise. In the world of image processing, image denoising is a crucial image-enhancing operation. This paper introduces and presents an improved denoising technique based on an adaptive ROAD-TGM-HT (rank order absolute difference-trimmed global mean Hough transform) filter that effectively eliminates high-density salt and pepper noise. The proposed approaches are evaluated using the MATLAB program. In qualitative and quantitative statistical analyses, performance metrics such as the Peak Signal to Noise Ratio, Image Enhancement Factor, and Structural Similarity Index have been utilized. Performing image denoising using these performance criteria. Grayscale and color pictures are utilized to test the Proposed Algorithm (PA), which offers an exceptional PSNR and IEF, especially at rising noise densities. This method considerably enhances image quality in comparison to prior techniques by efficiently reducing high-density noise produced during image acquisition or resulting from data transfer. To overcome this issue, we strengthened the ROAD-TGM by making it adaptable, and for the remaining pixels, we added the Hough Transform method, allowing it to perform better in scenarios with a high noise density. © 2022 The Author(s)
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共 35 条
  • [31] Singh A., Sethi G., Kalra G.S., Spatially adaptive image denoising via enhanced noise detection method for grayscale and color images, IEEE Access, 8, pp. 112985-113002, (2020)
  • [32] Enginoglu S., Erkan U., Memis S., Adaptive Cesáro mean filter for salt-and-pepper noise removal, El-Cezeri J. Sci. Eng., 7, 1, pp. 304-314, (2020)
  • [33] erkan U., Thanh D.N.H., Hieu L.M., Enginoglu S., An iterative mean filter for image denoising, IEEE Access, 7, pp. 167847-167859, (2019)
  • [34] Li F., AWMF for Salt and Pepper noise removal, MATLAB Central File Exchange, (2022)
  • [35] Memis S., Erkan U., Different adaptive modified Riesz mean filter for high-density salt-and-pepper noise removal in grayscale images, Eur. J. Sci. Technol., pp. 359-367, (2021)
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