Synthetic aperture radar (SAR) image interpretation is an important aspect of SAR processing. Speckle noises proliferate in SAR images. Given that speckles cause problems with the interpretation of SAR images

speckles must be reduced to obtain high-quality images in SAR follow-up processing. Edge preservation is also a crucial aspect to consider. However

these tasks are inconsistent. Therefore

an efficient algorithm is needed to solve this problem. To achieve speckle reduction and preserve edges

we propose speckle reduction based on Euclidean distance anisotropic diffusion. The main model of the proposed method of speckle reduction is based on SRAD method. SRAD is a modified P-M method

which can reduce additive noise. However

speckle noise is multiplicative noise. The modified P-M method

SRAD

can reduce multiplicative noise. Thus

anisotropic diffusion is successfully applied in SAR image processing. The current study proposed anisotropic diffusion based on a novel edge-detection method. First

to maintain edge information

edges were detected

which can be performed by Euclidean distance. The value of the Euclidean distance was lower than the set threshold. The pixel points that were used to compare the two sides were considered non-edge areas. Otherwise

the points belonged to the edge area. The threshold was set by calculating the mean of all Euclidean distances. Second

a new anisotropic diffusion coefficient function was established based on the results of the first step of the study. The coefficient function determined the scale of diffusion. The established mathematical model calculated the diffusing capacity of all pixel points in SAR images. Finally

the model of anisotropic diffusion was developed by following the SRAD method. The calculated results can update the intensity value of all pixel points in SAR images. Anisotropic diffusion exhibited new behaviors because Euclidean distance was used in Euclidean distance anisotropic diffusion. The accurate calculations of the mean value and variance of speckle noises were difficult to obtain and significantly influence the result of speckle reduction. The proposed method can avoid the estimation of the mean value and variance. This paper uses several anisotropic diffusion methods on two TanDEM-X images. The result showed that these methods can effectively reduce speckle noises when images contained weak speckle noises. However

the proposed method yielded better results when images contained strong speckle noises. Euclidean distance anisotropic diffusion can effectively maintain edge

unlike other methods. A novel method to reduce speckles in SAR images is proposed. This method is categorized as anisotropic diffusion and is called Euclidean distance anisotropic diffusion. Euclidean distance anisotropic diffusion is a modified SRAD method based on Euclidean distance. It combines the SRAD model with Euclidean distance to effectively reduce speckles. The experimental result showed that the method can reduce speckle noise in areas with high and low concentrations of noise speckles.