Adaptive Switching De-noising Filter Cascaded with Cuckoo Search Algorithm to Minimize the Mean Error – Medical Image Application

Authors

  • RamyaA Department of Computer Science & Engineering, Manonmaniam Sundaranar University, Tirunelveli, India.
  • Murugan D Department of Computer Science & Engineering, Manonmaniam Sundaranar University, Tirunelveli, India.
  • Kumar TG School of Computing Science & Engineering, Galgotia’s University, Greater Noida, India
  • Kumar V Department of Computer Applications, NPR Arts and Science College, Natham, India

Keywords:

Switching filter, image de-noising, impulse noise, optimization technique, Cuckoo search algorithm

Abstract

This paper presented the new work to minimize the mean absolute error of mammogram breast image which is highly corrupted by impulse noise density. The proposed methodology is implemented with the Adaptive Switching Weighted Median (ASWM) Filter cascaded with Cuckoo Search (CS) optimization algorithm. The efficient adaptive filter de-noises the medical image by detecting the corrupted pixel and replaces them with the median value. The CS algorithm minimizes the error rate between the ASWM filter image and corrupted image. It minimizes the Mean Absolute Error (MAE) percentage and also maximizes the Peak Signal to Noise Ratio (PSNR). This method removes the highly corrupted impulse noise of 90%. The experimental analysis is made and it is observed from the result that the proposed method is far superior to the other conventional techniques in terms of qualitative and quantitative factors. In terms of visual quality, it yields a well sharp edge region and better visual perception of the image quality.

References

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Published

2025-11-13

How to Cite

[1]
A. Ramya, D. Murugan, T. G. Kumar, and V. Kumar, “Adaptive Switching De-noising Filter Cascaded with Cuckoo Search Algorithm to Minimize the Mean Error – Medical Image Application”, Int. J. Comp. Sci. Eng., vol. 6, no. 4, pp. 1–7, Nov. 2025.

Issue

Vol. 6 No. 4 (2018): IJCSE Special Issue May Edition

Section

Research Article

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