sis 22(4): 17

Research Article

An Efficient Algorithm for Image De-noising by using Adaptive Modified Decision Based Median Filters

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  • @ARTICLE{10.4108/eai.27-1-2022.173163,
        author={Faiz Ullah and Kamlesh Kumar and Mansoor Ahmed Khuhro and Asif Ali Laghari and Asif Ali Wagan and Umair Saeed},
        title={An Efficient Algorithm for Image De-noising by using Adaptive Modified Decision Based Median Filters},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        keywords={Image De-nosing, Spatial Filtering, Salt and Pepper Noise},
  • Faiz Ullah
    Kamlesh Kumar
    Mansoor Ahmed Khuhro
    Asif Ali Laghari
    Asif Ali Wagan
    Umair Saeed
    Year: 2022
    An Efficient Algorithm for Image De-noising by using Adaptive Modified Decision Based Median Filters
    DOI: 10.4108/eai.27-1-2022.173163
Faiz Ullah1,*, Kamlesh Kumar1, Mansoor Ahmed Khuhro1, Asif Ali Laghari1, Asif Ali Wagan1, Umair Saeed1
  • 1: Sindh Madressatul Islam University
*Contact email:


This article has been retracted, and the retraction notice can be found here: 

INTRODUCTION: In image processing noise removal is a hot research field. Lots of studies have been carried out and many algorithms and filters have been planned to improve the image information. There are various noise removal procedures to identify and remove the corrupted pixels. But several image de-noising algorithms apply the filter to the overall image to filter non-corrupted pixels also. To overcome these weaknesses, we proposed an efficient denoising algorithm by cascading Adaptive Median Filter (AMF) with Modified Decision Based Median Filter (MDBMF). OBJECTIVES: To acquire an efficient denoising algorithm for impulse noise reduction by combining AMF and MDBMF methods which are effective, efficient for denoising various kinds of images. To retain the edges, prevent signal deterioration, and ensure non-corrupted image pixels are remaining intact, regardless of various degrees of noise in the image. To avoid the condition where noisy pixels are replaced by other noisy pixels to maintain the quality of images from its degraded noise version such as blur which often takes place during transmission, acquisition, storage, etc. METHODS, RESULTS AND CONCLUSION: The performance corroboration of the proposed efficient denoising algorithmis accomplished employing nine standard grayscale images. The size of all standard images kept 256x256 pixels in this research. The proposed image denoising system has experimented on those images affected with 10% to 90% salt & pepper noise density. Additionally, the performance of the existing state-of-art denoising techniques like AMF, MF, WMF, UMF, and DBMF are contrasted with the proposed hybrid approach. The results showed that de-noised images obtained for 10% to 90% densities levels by proposed hybrid approach are quite better than the quality of denoised images achieved from WMF, UTMF, AMF, and DBMF methods. The proposed algorithm effectively eradicates salt and pepper noise for lower to higher image noise densities levels.