Abstract
For the de-noising process of cattle follicle ultrasound images, we need to retain the edge details containing important information while removing the speckle noise. According to the traditional de-noising method, the PM anisotropic diffusion model in the selection of diffusion coefficient and diffusion threshold K properly, resulting in poor smoothing effect of ultrasound images, image detail preserving problems and other related issues, this paper proposes an improved anisotropic diffusion filtering algorithm based on several current typical anisotropic diffusion filtering. In this paper, the gradient mode of the adaptive median filter is used to replace the gradient mode of the original image, in addition, the diffusion coefficient and the selection of the diffusion threshold are also improved. PSNR, SSIM, homogeneity region contrast, and edge retention capability FOM are used to evaluate the quality of the algorithm. The experimental results show that the improved method can effectively suppress the noise of the cattle follicle ultrasonic image and better retain the edge details, providing a good basis for the subsequent processing of images.
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Lv, Y., Liu, J. (2018). An Improved Anisotropic Diffusion of Cattle Follicle Ultrasound Images De-noising Algorithm. In: Huang, DS., Gromiha, M., Han, K., Hussain, A. (eds) Intelligent Computing Methodologies. ICIC 2018. Lecture Notes in Computer Science(), vol 10956. Springer, Cham. https://doi.org/10.1007/978-3-319-95957-3_45
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DOI: https://doi.org/10.1007/978-3-319-95957-3_45
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