BAI Jian, FENG Xiangchu. Image Denoising and Decomposition Using Non-convex Functional[J]. Chinese Journal of Electronics, 2012, 21(1): 102-106.
Citation: BAI Jian, FENG Xiangchu. Image Denoising and Decomposition Using Non-convex Functional[J]. Chinese Journal of Electronics, 2012, 21(1): 102-106.

Image Denoising and Decomposition Using Non-convex Functional

  • Received Date: 2011-07-01
  • Rev Recd Date: 2011-09-01
  • Publish Date: 2012-01-05
  • This paper proposes a new model for image denoising and decomposition by non-convex functional minimization. Instead of using the Banach norm as the fidelity term, we use the square of L2 norm of the residual component divided by BV semi-norm as the fidelity term. This non-convex fidelity term has very low value for the texture image and high value for the geometric image, so it is appropriate for image denoising and decomposition. The gradient descent procedure is used to solve the proposed minimization problem, which leads to evolve a new nonlinear integral-differential equation to steady state. The experimental results demonstrate the proposed model not only obtains higher SNR but also makes visual improvements compared with the classical TV and OSV models.
  • loading
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (573) PDF downloads(887) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return