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Performance Evaluation of De-noising Techniques Using Full-Reference Image Quality Metrics

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Computing, Analytics and Networks (ICAN 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 805))

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Abstract

The de-noising of digital images is crucial preprocessing step before moving toward image segmentation, representation and object recognition. It is an important to find out efficacy of filter for different noise models because filtering operation is application oriented task and performance varies according to type of noise present in images. A comparative study is made to elucidate the behavior of different spatial filtering techniques under different noise models. In this paper different types of noises like Gaussian noise, Speckle noise, Salt & Pepper noise is applied on grayscale standard image of Lenna and using spatial filtering techniques the values of full reference based image quality metrics are found and compared in tabular and graphical form. The outcome of comparative study shows that Lee, Kuan and Anisotropic Diffusion Filter worked well for Speckle noise, the Salt and Pepper noise has significantly reduced using Median and AWMF, and the Mean filter and Wiener filter works immensely efficient for reducing Gaussian noise.

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Acknowledgement

The authors express their sincere gratitude to I.K.G Punjab Technical University, kapurthala for their support and motivation.

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Authors and Affiliations

  1. I.K.G Punjab Technical University, Kapurthala, India

    Palwinder Singh

  2. Global Institute of Management and Emerging Technologies, Amritsar, 143001, India

    Leena Jain

Authors
  1. Palwinder Singh
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  2. Leena Jain
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Corresponding author

Correspondence to Palwinder Singh .

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Editors and Affiliations

  1. Chitkara University, Chandigarh, India

    Rajnish Sharma

  2. Chitkara University, Chandigarh, India

    Archana Mantri

  3. Department of Computer Science and Electrical Engineering, Louisiana Tech University, Ruston, Louisiana, USA

    Sumeet Dua

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Singh, P., Jain, L. (2018). Performance Evaluation of De-noising Techniques Using Full-Reference Image Quality Metrics. In: Sharma, R., Mantri, A., Dua, S. (eds) Computing, Analytics and Networks. ICAN 2017. Communications in Computer and Information Science, vol 805. Springer, Singapore. https://doi.org/10.1007/978-981-13-0755-3_1

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  • DOI: https://doi.org/10.1007/978-981-13-0755-3_1

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-0754-6

  • Online ISBN: 978-981-13-0755-3

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