3 years ago

Iterative Adaptive Unsymmetric Trimmed Shock Filter for High-Density Salt-and-Pepper Noise Removal

T. Veerakumar, Badri Narayan Subudhi, S. Esakkirajan, Prasanta Kumar Pradhan


In this paper, an iterative adaptive unsymmetric trimmed shock filter based on partial differential equations (PDE) is proposed to remove high-density salt-and-pepper noise by preserving the edge details in the images. This algorithm consists of two steps: identification of pixels affected by the salt-and-pepper noise and recovery of these noisy pixels using adaptive unsymmetric trimmed shock filter. Shock filter has been used in image processing literature for image restoration and enhancement task. However, its use was limited to unwanted noise removal, enhancement, despeckling, etc. In the proposed work, a modified form of shock filter termed as adaptive unsymmetric trimmed shock filter is designed to remove the salt-and-pepper noise. The proposed algorithm is tested with different test images. Three performance evaluation measures: PSNR, CR and MSSIM are used to validate the proposed scheme. The performance of the proposed algorithm claims better results than the other considered eight existing state-of-the-art techniques.

Publisher URL: https://link.springer.com/article/10.1007/s00034-018-0984-4

DOI: 10.1007/s00034-018-0984-4

You might also like
Discover & Discuss Important Research

Keeping up-to-date with research can feel impossible, with papers being published faster than you'll ever be able to read them. That's where Researcher comes in: we're simplifying discovery and making important discussions happen. With over 19,000 sources, including peer-reviewed journals, preprints, blogs, universities, podcasts and Live events across 10 research areas, you'll never miss what's important to you. It's like social media, but better. Oh, and we should mention - it's free.

  • Download from Google Play
  • Download from App Store
  • Download from AppInChina

Researcher displays publicly available abstracts and doesn’t host any full article content. If the content is open access, we will direct clicks from the abstracts to the publisher website and display the PDF copy on our platform. Clicks to view the full text will be directed to the publisher website, where only users with subscriptions or access through their institution are able to view the full article.