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Color Photo Denoising Via Hue, Saturation and Intensity Diffusion

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Image Analysis and Recognition (ICIAR 2008)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5112))

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Abstract

This paper presents a new image denoising model for color photo noise removal. Unlike previous approaches, our algorithm is based on separating a color photo into hue, saturation, and intensity (HSI) components, and then processing each component with partial differential equations (PDE)-based diffusion flows. The hue and saturation denoising are implemented by a new weighted orientation diffusion and a modified curvature flow respectively. The intensity denoising is implemented with a PDE that is a combination of a gradient vector flow (GVF)-based filter and a fourth-order PDE filter. This combined technique provides a robust and accurate denoising process, i.e., it preserves edges well and at the same time overcomes the staircase effect in smooth regions. Experiments on color photos demonstrate the improved performance of the proposed model when compared with other recognized approaches and commercial software.

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Author information

Authors and Affiliations

  1. Information Technology Department, Armstrong Atlantics State University, 11935 Abercorn Street, Savannah, Georgia, USA, 31419

    Lei He

  2. Imaging and Visualization Department, Siemens Corporate Research, 755 College Road East, Princeton, New Jersey, USA, 08540

    Chenyang Xu

Authors
  1. Lei He
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  2. Chenyang Xu
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Editor information

Aurélio Campilho Mohamed Kamel

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© 2008 Springer-Verlag Berlin Heidelberg

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He, L., Xu, C. (2008). Color Photo Denoising Via Hue, Saturation and Intensity Diffusion. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2008. Lecture Notes in Computer Science, vol 5112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69812-8_16

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  • DOI: https://doi.org/10.1007/978-3-540-69812-8_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69811-1

  • Online ISBN: 978-3-540-69812-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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