Passive Millimeter Wave Image Denoising Based on Adaptive Manifolds

نویسندگان

  • Shujin Zhu
  • Yuehua Li
  • Jianfei Chen
  • Yuanjiang Li
چکیده

Since the characters of poor inherent resolution and low signal-to-noise limit the application of the passive millimeter wave (PMMW) image, it is particularly important to improve the resolution and denoise the PMMW image. In this paper, the adaptive manifolds filtering algorithm based on non-local means (AM-NLM) is illustrated in detail. And an improved version of AM-NLM filtering algorithm is proposed for processing the PMMW image. The proposed algorithm firstly applies the AM-NLM filtering to obtain the basic denoised PMMW image. Then the image enhancement based on Laplacian of Gaussian operator is performed to enhance the edge of the target in PMMW image. Finally, the hard-threshold filtering with different thresholds is adopted to filter each dimension to achieve the final filtering response. Experimental results have shown that the proposed PMMW filtering algorithm has better and more satisfactory performance compared to AM-NLM, both in subjective visual effect and objective image quality metric. Additionally, our proposed algorithm is also available for real PMMW images.

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تاریخ انتشار 2013