Speckle noise reduction is a key problem of the image analysis of medical UltraSound images. In this paper, two important improvements have been developed to a fast anisotropic diffusion algorithm for speckle noise re...Speckle noise reduction is a key problem of the image analysis of medical UltraSound images. In this paper, two important improvements have been developed to a fast anisotropic diffusion algorithm for speckle noise reduction. The Gaussian filter is firstly used before gradient calculation, and then the adaptive algorithm of the factor k is proposed. Numerous experimental results show that the proposed model is superior to other methods in noise removal, fidelity and edge preservation. It is suitable for the preprocessing of a great number of medical UltraSound images, such as three dimen- sional reconstruction.展开更多
In general there is a digital image with noise, low contrast, blnrred edges and other defects. To effectively enhance the contrast of the image blur to meet the requirements of the subsequent identification and detect...In general there is a digital image with noise, low contrast, blnrred edges and other defects. To effectively enhance the contrast of the image blur to meet the requirements of the subsequent identification and detection. This paper presents a fuzzy adaptive image contrast enhancement algorithm based on gray entropy. This method not only enhances the overall image contrast, but also effectively enrich the target image detail information, and suppress the noise amplification. Meanwhile, the paper proposes an improved K and P parameters image restoration algorithm. The algorithm combines both isotropic and anisotropic diffusion, the use of regional differences in the frequency achieved in the different regions use different iterative equation. Experimental results show that the algorithm with TV model algorithm compared with the same premise of restorative effects, avoiding the staircase effect and better than the TV model repair speed.展开更多
Speckle noise has long been known as a limiting factor for the quality of an ultrasound B-mode image.In this study,anisotropic diffusion filtering is proposed as an effective method for ultrasound speckle reduction.Th...Speckle noise has long been known as a limiting factor for the quality of an ultrasound B-mode image.In this study,anisotropic diffusion filtering is proposed as an effective method for ultrasound speckle reduction.This article provides a brief description of anisotropic diffusion filtering proposed by Perona and Malik,and compares its speckle filtering effects with other filtering methods including median,moving average,and frequency domain Gaussian low-pass.In this study,multiple filters are implemented in Matlab.For each filter,three different types of noisy images with speckle noise are tested.The results show that anisotropic filter can reduce the noise more effectively and meanwhile preserve the boundaries of the objects.In addition,this filter has more controllable filtering parameters and is independent on the information of the noise.展开更多
基金Supported by National Natural Science Foundation of China (No.60272060)Doctoral Foundation of Ministry of Education (No.20030610032)Sichuan Youth Science and Technology Foundation (No.04ZQ026-013).
文摘Speckle noise reduction is a key problem of the image analysis of medical UltraSound images. In this paper, two important improvements have been developed to a fast anisotropic diffusion algorithm for speckle noise reduction. The Gaussian filter is firstly used before gradient calculation, and then the adaptive algorithm of the factor k is proposed. Numerous experimental results show that the proposed model is superior to other methods in noise removal, fidelity and edge preservation. It is suitable for the preprocessing of a great number of medical UltraSound images, such as three dimen- sional reconstruction.
文摘In general there is a digital image with noise, low contrast, blnrred edges and other defects. To effectively enhance the contrast of the image blur to meet the requirements of the subsequent identification and detection. This paper presents a fuzzy adaptive image contrast enhancement algorithm based on gray entropy. This method not only enhances the overall image contrast, but also effectively enrich the target image detail information, and suppress the noise amplification. Meanwhile, the paper proposes an improved K and P parameters image restoration algorithm. The algorithm combines both isotropic and anisotropic diffusion, the use of regional differences in the frequency achieved in the different regions use different iterative equation. Experimental results show that the algorithm with TV model algorithm compared with the same premise of restorative effects, avoiding the staircase effect and better than the TV model repair speed.
基金supported by the Fundamental Research Funds for the Central Universities(Grant No.NS2014060)
文摘Speckle noise has long been known as a limiting factor for the quality of an ultrasound B-mode image.In this study,anisotropic diffusion filtering is proposed as an effective method for ultrasound speckle reduction.This article provides a brief description of anisotropic diffusion filtering proposed by Perona and Malik,and compares its speckle filtering effects with other filtering methods including median,moving average,and frequency domain Gaussian low-pass.In this study,multiple filters are implemented in Matlab.For each filter,three different types of noisy images with speckle noise are tested.The results show that anisotropic filter can reduce the noise more effectively and meanwhile preserve the boundaries of the objects.In addition,this filter has more controllable filtering parameters and is independent on the information of the noise.
