@article{scholars16054,
       publisher = {Ismail Saritas},
         journal = {International Journal of Intelligent Systems and Applications in Engineering},
           pages = {743--751},
            year = {2022},
           title = {An Efficient Low Complexity Salt \& Pepper Noise Detection Method},
          number = {4},
          volume = {10},
            note = {cited By 0},
        abstract = {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. {\^A}{\copyright} 2022, Ismail Saritas. All rights reserved.},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164825844&partnerID=40&md5=693902eabce6b3537f0ffcc4e91c5e44},
          author = {Khan, S. and Khan, M. A. and Alsughayyir, A. and Alshanqiti, A. and Talpur, B. A. and Gilal, A. R.},
            issn = {21476799}
}