The use of Different Filters and their effects on Convolution with Grayscale Images

Abstract

Computer vision is ubiquitous in the world today, starting from unlocking phones to robots performing complex surgeries in hospitals and managing the assembly line in factories. In this paper, the focus has been placed on the use of filters or kernels or masks and their effects when convolved with grayscale images.

Introduction

Conclusion

These are some of the crude techniques employed in computer vision. Of course, when you turn on the filtering option on your smartphone cameras, or the night-mode on your smartphone captures superb images even in extremely low-light conditions, there are much more sophisticated algorithms at work. But, all sophisticated algorithms at play in modern day devices stem from these algorithms, which make their study even more worthwhile.

References

[1] Digital Image Processing, Gonzalez, R and Woods, R., Prentice Hall [2] Computer Vision Algorithms and Applications, Szeliski, R., Springer [3] R.A. Haddad and A.N. Akansu, \"A Class of Fast Gaussian Binomial Filters for Speech and Image Processing,\" IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 39, pp 723–727, March 1991 [4] Diggle, P. J. (1985), \"A kernel method for smoothing point process data\", Journal of the Royal Statistical Society, Series C, 34 (2): 138–147 [5] Uludag, A. M. (1998), \"On possible deterioration of smoothness under the operation of convolution\", J. Math. Anal. Appl., 227 (2): 335–358 [6] Huang, Thomas S.; Yang, George J.; Tang, Gregory Y. (February 1979). \"A fast two-dimensional median filtering algorithm\" (PDF). IEEE Transactions on Acoustics, Speech, and Signal Processing. 27 (1): 13–18 [7] Arias-Castro, Ery; Donoho, David L. (June 2009). \"Does median filtering truly preserve edges better than linear filtering?\". Annals of Statistics. 37 (3): 1172–2009.

Copyright

Copyright © 2022 Abhik Biswas. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.