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An Improved Approach for Removal of Salt and Pepper Noise in MR Images

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Advances in Deep Learning, Artificial Intelligence and Robotics

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 249))

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Abstract

Removal of the noise entirely is the most intricate process, as it sometimes ruins the visual excellence of image along with its details. So, the exclusion of noise is imperative for the better quality of images. Noisy pixels also reserves the memory; that space is unnecessary reserved for senseless data. Noise added in an image during image acquisition mostly. In this manuscript, we present an efficient method for removing salt and pepper noise using the modified weighted mean filter. It includes noise identification and removal processes from the Magnetic Resonance Images. And reproduce an enhanced de-noised image. In the proposed method, we use the cosine rule for detecting the noisy pixel and replaced by their mean value within a window size 3\(\times \)3. Similarly, we applied the proposed methods on various filters like alpha trimmed filter, mean, mode and median filter and all the filters give promising results. Experiment results indicate efficiency over other approaches in removing salt-and-pepper noise.

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Author information

Authors and Affiliations

  1. Central University of Rajasthan, Ajmer, Rajasthan, India

    Monika Jyotiyana & Nishtha Kesswani

  2. Anand ICE, Jaipur, Rajasthan, India

    Anupam Agarwal

Authors
  1. Monika Jyotiyana
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  2. Nishtha Kesswani
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  3. Anupam Agarwal
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Editor information

Editors and Affiliations

  1. Department of Management and Innovation Systems, University of Salerno, Fisciano, Italy

    Luigi Troiano

  2. Department of Engineering, University of Sannio, Benevento, Italy

    Alfredo Vaccaro

  3. Department of Management and Innovation Systems, University of Salerno, Fisciano, Italy

    Roberto Tagliaferri

  4. Department of Computer Science, Central University of Rajasthan, Ajmer, Rajasthan, India

    Nishtha Kesswani

  5. Department of Computer Science, University of Oviedo, Gijón, Spain

    Irene Díaz Rodriguez

  6. Emlyon Business School, Écully, France

    Imene Brigui

  7. Department of Management and Innovation Systems, University of Salerno, Fisciano, Italy

    Domenico Parente

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Jyotiyana, M., Kesswani, N., Agarwal, A. (2022). An Improved Approach for Removal of Salt and Pepper Noise in MR Images. In: Troiano, L., et al. Advances in Deep Learning, Artificial Intelligence and Robotics. Lecture Notes in Networks and Systems, vol 249. Springer, Cham. https://doi.org/10.1007/978-3-030-85365-5_11

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