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Image Denoising Using Wavelet Transform Based Flower Pollination Algorithm

  • B. V. D. S. SekharEmail author
  • S. Venkataramana
  • V. V. S. S. S. Chakravarthy
  • P. S. R. Chowdary
  • G. P. S. Varma
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 862)

Abstract

Image Denoising is a consistent problem from long period of time and still a challenging task for researchers. There evolved many techniques for image denoising which involves filtering techniques in spatial domain, Transform techniques in transform domain (Sekhar et al. in IRECOS 10(10):1012–1017, 2015 [1]), and more recently evolutionary computing tools (ECT) and genetic algorithms proved more effective in denoising of images. There are many ECT available which can be applied for denoising problem (Sekhar et al. in JGIM 25(4) 2017, [2]). In this paper we made an attempt to Denoise both color and grayscale images by applying a new ECT which emerged out with more efficient results. Peak Signal to noise ratio (PSNR), Structural Similarity Index Metric (SSIM), Mean Structural Similarity Index Metric (MSSIM), etc., are considered in this paper as Image quality Assessment metrics. Comparison of proposed method is also compared with state-of-the-art techniques.

Keywords

Image denoising Evolutionary computing tools (ECT) Flower pollination algorithm (FPA) Optimization Wavelet transforms Peak signal to noise ratio (PSNR) Structural similarity index metric (SSIM) Mean structural similarity index metric (MSSIM) 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • B. V. D. S. Sekhar
    • 1
    Email author
  • S. Venkataramana
    • 1
  • V. V. S. S. S. Chakravarthy
    • 2
  • P. S. R. Chowdary
    • 2
  • G. P. S. Varma
    • 1
  1. 1.Department of Information TechnologyS.R.K.R Engineering CollegeBhimavaramIndia
  2. 2.Department of Electronics and Communication EngineeringRaghu Institute of TechnologyVisakhapatnamIndia

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