An Efficient Low Complexity Salt & Pepper Noise Detection Method


  • Sajid Khan Department of Computer Science, School of Engineering, Akfa University, Tashkent, Uzbekistan
  • Muhammad Asif Khan Department of Computer Science, Sukkur IBA University, Sukkur, Pakistan
  • Abdul Rehman Gilal Department of Computer and Information Sciences, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia
  • Aeshah Alsughayyir College of Computer Science and Engineering, Taibah University, Kingdom of Saudi Arabia
  • Abdullah Alshanqiti Faculty of Computer and Information Systems, Islamic University, Kingdom of Saudi Arabia
  • Bandeh Ali Talpur School of Computer Science and Statistics, Trinity College Dublin, Ireland


Impulse noise, Image restoration, salt & pepper noise, Morphological filtering.


A new impulse noise detection algorithm is proposed in this paper. The most popular method for detection of impulse noise is to classify every pixel with intensity 0 or 255 as noise. Other techniques involve the detection of noise candidates in the first stage followed by false-positive reduction process in the second stage. Both types of techniques have some problems such as the first approach fails to distinguish between a noisy pixel and pure white or black background region. The second type detection algorithm often results in the detection of an unwanted amount of false positives. They also demand more CPU elapsed time. The proposed method is a two-stage impulse noise detector that first detects all the true positives along with false positives that are the result of the appearance of pure white or pure black uniform regions in the image. It then applies morphological operators such as erosion and pixel connectivity to avoid the detection of uniform regions as noisy pixels. Simulation results show that the proposed impulse noise detector method outperformed existing noise detection methods. The proposed method can be applied as an initial noise detection step for the removal of salt & pepper noise using any spatial filter.


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Densities of pixels with non-noisy 0 and 255 intensities in each of 47 images.




How to Cite

Sajid Khan, Muhammad Asif Khan, Abdul Rehman Gilal, Aeshah Alsughayyir, Abdullah Alshanqiti, & Bandeh Ali Talpur. (2022). An Efficient Low Complexity Salt & Pepper Noise Detection Method. International Journal of Intelligent Systems and Applications in Engineering, 10(4), 743–751. Retrieved from



Research Article