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Multispectral Image Denoising Based on Non-local Means and Bilateral Filtering

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Internet Multimedia Computing and Service (ICIMCS 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 819))

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Abstract

Multispectral images are obtained by taking multiple images of the different wave bands of the same target, which provides a more comprehensive and clearer description of the scene. However, in practice, multispectral images are always degraded by various types of noise. In this paper, an image denoising method based on non-local means and bilateral filtering is proposed. The method uses the non-local means algorithm to denoise the image, and then uses the bilateral filter to enhance it. The proposed method is compared with the BM3D denoising algorithm, non-local means algorithm and bilateral filtering. The experimental results show that the proposed method not only improves the visual effect but also the value of structural similarity and feature similarity.

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Notes

  1. 1.

    http://www1.cs.columbia.edu/CAVE/databases/multispectral.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (Grant Nos. 61370138, 61572077, 61271435, and U1301251) and Beijing Municipal Natural Science Foundation (Grant Nos. 4152017 and 4162027).

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Correspondence to Ning He .

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Zhen, X., He, N., Sun, X., Zhang, Y. (2018). Multispectral Image Denoising Based on Non-local Means and Bilateral Filtering. In: Huet, B., Nie, L., Hong, R. (eds) Internet Multimedia Computing and Service. ICIMCS 2017. Communications in Computer and Information Science, vol 819. Springer, Singapore. https://doi.org/10.1007/978-981-10-8530-7_37

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  • DOI: https://doi.org/10.1007/978-981-10-8530-7_37

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8529-1

  • Online ISBN: 978-981-10-8530-7

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