Shearlet transform and fast bilateral filter image denoising method

Abstract

The invention discloses a shearlet transform and fast bilateral filter image denoising method, which comprises the steps of: 1) acquiring an envelope signal of a noise image by using a noise imaging system, and establishing a medical ultrasonic image model; 2) carrying out multiscale and multidirectional decomposition on the medical ultrasonic image model after logarithmic transformation obtained in the step 1) by utilizing a pyramid filter bank; 3) performing threshold method contraction processing on a two-dimensional discrete shearlet transform coefficient of a high-frequency part in each subband image obtained in the step 2); 4) using a fast bilateral filter for filtering shearlet coefficients of low-frequency parts in the step 2); 5) and conducting shearlet inverse transform processing on all the coefficients processed in the step 3) and the step 4), so as to obtain a denoised medical ultrasound images. The introduction of the fast bilateral filter in the shearlet transform and fast bilateral filter image denoising method can effectively improve the denoising performance, and greatly increase the processing efficiency.

Description

technical field [0001] The invention relates to a shearlet transform and a fast bilateral filter image denoising method. The invention belongs to the field of denoising of medical ultrasound images, and in particular refers to a method of denoising the medical ultrasound images based on shearlet transformation and fast bilateral filter. Background technique [0002] In the field of medical imaging, imaging technologies such as ultrasound imaging, CT, and MRI have been applied in medical clinical diagnosis. The application of ultrasound diagnosis as a diagnostic technique in medical diagnosis began in 1972 with the advent of grayscale ultrasound. Especially in recent years, ultrasound diagnosis has been widely used in medical clinical diagnosis, especially in the observation of fetal growth in pregnant women and In clinical applications such as the diagnosis of abdominal organ lesions, the use of ultrasound imaging technology is more important. [0003] However, in the clin...

AI Technical Summary

Problems solved by technology

Wavelet analysis lays the foundation for the sparseness of signals and images. Wavelet transform can optimally approximate the zero-Vitch heterogeneity, but its excellent performance is difficult to extend to two-dimensional images and higher data spaces.

[0006] The theory of multi-scale geometric analysis overcomes the insufficiency of wavelet analysis in dealing with sparse high-dimensional data

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