Ultrasonic Images Denoising Based on Calculus of Variations

The presence of speckle noise in medical ultrasound images not only reduces the image quality and affects the diagnosis results, but also brings difficulties to the subsequent processing such as image edge detection and feature extraction. Therefore, how to effectively remove speckle noise is of great significance to the research on enhancing the quality of medical ultrasound images and clinical application. In this paper, we propose a new method to remove speckle noise from ultrasonic images based on calculus of variations. The innovation of this method lies in the introduction of anisotropic diffusion equation of partial differential equation. Therefore, this method not only considers the effect of removing speckle noise, but also can well preserve the edge features of the image. Firstly, logarithmic transformation is carried out on ultrasonic images to convert multiplicative noise into additive noise. Then, calculus of variations is applied to the image after logarithmic transformation. Finally, the ultrasonic image is reconstructed by exponential transformation. In the denoising experiment, calculus of variations is compared with mean filtering, median filtering, wiener filtering and wavelet transform. The experimental results show that the denoising performance of the calculus of variations is obviously better than other methods.