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Comparative performance analysis of spatial domain filtering techniques in digital image processing for removing different types of noise | ||
| International Journal of Nonlinear Analysis and Applications | ||
| دوره 13، Special Issue for selected papers of ICDACT-2021، خرداد 2022، صفحه 117-125 اصل مقاله (407.24 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2022.6337 | ||
| نویسندگان | ||
| Prashant Kumar Dubey* 1؛ Pratima Dubey1؛ Mayank Sharma2؛ Soni Changlani3 | ||
| 1Department of Electronics and Comm. Engineering, S. V. Polytechnic College, Bhopal, (M.P.), India | ||
| 2Mathematics Division, SASL, VIT University Bhopal, (M.P.), India | ||
| 3Department of Electronics and Comm. Engineering, LNCT College, Bhopal (M.P.), India | ||
| تاریخ دریافت: 24 مرداد 1401، تاریخ بازنگری: 01 دی 1400، تاریخ پذیرش: 25 دی 1400 | ||
| چکیده | ||
| The reduction of the noise of the images always prevails as a challenge in the field of image processing. An image obtained after the elimination of noise has a higher clarity in terms of interpretation and study analysis in different fields such as medical, satellite and radar. This research work examines the various methods of de-noise images in the spatial domain and a comparison between several filtering techniques is carried out in the presence of different types of noise to achieve a high-quality image and to find the most suitable and reliable method for De-noising images. performance of all the filters is compared using parameters such as Mean Square Error (MSE), peak signal to noise ratio (PSNR). | ||
| کلیدواژهها | ||
| image Processing؛ noise Removal؛ filtering techniques؛ mean square error (MSE)؛ signal to noise ratio(SNR)؛ Peak Signal noise ratio(PSNR) | ||
| مراجع | ||
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[1] P. Kaur and J. Singh, A study effect of Gaussian noise on PSNR value for digital images, Int. J. Comput. Electric. Engin. 3 (2011), no. 2, 1793–8163. [2] C. Mythili and V. Kavitha, Efficient technique for color image noise reduction, Res. Bull. Jordan ACM 2 (2011), no. 3, 41–44. [3] A. Agrawal and R. Raskar, Optimal single image capture for motion deblurring, Proc. IEEE Conf. Comput. Vision Pattern Recogn., 2009, p. 2560–2567. [4] P. Patidar, M. Gupta, S. Srivastava and A.K. Nagawat, Image de-noising by various filters for different noise, Int. J. Comput. Appl. 9 (2010), no. 4, 45–50. [5] C. Boncelet, Image noise models, Alan C. Bovik. Handbook of Image and Video Processing, 2005. [6] M. Salem, and D.N. Saleh Al-Amri, Comparative study of removal noise from remote sensing image, Int. J. Comput. Sci. Issues 7 (2010), no. 1. [7] K. Dabov, A. Foi, V. Katkovnik and K. Egiazarian, Image denoising by sparse 3D transform-domain collaborative filtering, IEEE Trans. Image Process. 16 (2007), no. 8, p. 2080–2095. [8] A. Danielyan, V. Katkovnik and K. Egiazarian, Senior member, IEEE “BM3D frames and variational image deblurring, Image Process. IEEE Trans. 21, no. 4. [9] D. Maheswari and V. Radha, Noise removal in compound image using median filter, Int. J. Comput. Sci. Engin. 2 (2010), no. 4, 1359–1362. [10] C.G. Rafael, Image restoration and reconstruction, Digital Image Process. 3rd ed. India: Pearson Prentice Hall, 2011, p. 322–330. | ||
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