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Image representation method based on Gaussian function and non-uniform partition

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Abstract

Image representation or reconstruction methods are important in digital image processing. Due to different image features happening in different regions, in this work, an image representation algorithm based on Gaussian function and non-uniform partition is proposed to represent the image with different functions in non-uniform regions. That means the pixel values in each region can be approximated by an extension of the Gaussian function after applying the least square approximation. The experimental results prove that the proposed algorithm has better performance than other non-uniform partition algorithms in terms of reconstructed image quality and time complexity. In addition, the partition mesh density can reflect the texture complexity of image regions and help to determine where the watermark can be embedded. Therefore, a novel watermark algorithm based on the proposed non-uniform partition is constructed and tested. The results show that it can embed a big gray watermark into the host image without causing its obvious distortion. This indicates some of the advantages of the proposed image representation algorithm.

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Acknowledgements

This work was supported by Macau University of Science and Technology Foundation (Grant numbers FRG-21-020-FI).

Funding

This study was funded by Macau University of Science and Technology Foundation (Grant numbers FRG-21-020-FI).

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Authors and Affiliations

  1. School of Computer Science and Engineering, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau, China

    WeiKang Zhao, KinTak U & HuiBin Luo

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  1. WeiKang Zhao
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  2. KinTak U
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  3. HuiBin Luo
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Correspondence to WeiKang Zhao.

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Zhao, W., U, K. & Luo, H. Image representation method based on Gaussian function and non-uniform partition. Multimed Tools Appl 82, 839–861 (2023). https://doi.org/10.1007/s11042-022-13213-3

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