A Novel Speckle Suppression Method with Quantitative Combination of Total Variation and Anisotropic Diffusion PDE Model

Jiamu Li,Zhongjun Yu,Zijian Wang,Wenbo Yu,Yunhua Luo

doi:10.3390/rs14030796

Abstract

Speckle noise seriously affects synthetic aperture radar (SAR) image application. Speckle suppression aims to smooth the homogenous region while preserving edge and texture in the image. A novel speckle suppression method based on the combination of total variation and partial differential equation denoising models is proposed in this paper. Taking full account of the local statistics in the image, a quantization technique—which is different from the normal edge detection method—is supported by the variation coefficient of the image. Accordingly, a quantizer is designed to respond to both noise level and edge strength. This quantizer automatically determines the threshold of diffusion coefficient and controls the weight between total variation filter and anisotropic diffusion partial differential equation filter. A series of experiments are conducted to test the performance of the quantizer and proposed filter. Extensive experimental results have demonstrated the superiority of the proposed method with both synthetic images and natural SAR images.

Highlights

Speckle noise exists inherently in active imaging systems such as synthetic aperture radar (SAR) and ultrasonic scanning image systems [1]
Different from the existing edge detectors, we propose a quantizer based on the local variation coefficient of image in two size-adaptive concentric windows, to quantify the relationship between each pixel with image features and provide guidance for diffusion coefficient and final combination model
The experimental results presented in the previous section show that the quantitative anisotropic diffusion (QAD) method method proposed in this paper possesses great de-speckling ability, both in the aspects of proposed in this paper possesses great de-speckling ability, both in the aspects of smoothing smoothing and feature-preservation

Summary

Introduction

Speckle noise exists inherently in active imaging systems such as synthetic aperture radar (SAR) and ultrasonic scanning image systems [1]. Speckle is commonly interpreted as a kind of locally correlated noise that reduces image contrast and conceals fine feature details, causing negative effects on target detection and recognition [2,3] scene segmentation [4], and image registration [5]. In consideration of the damaging effect of speckle on images, speckle suppression is required to smooth uniform areas of the images and preserve the features, like edges and textures. Feature-preserving speckle suppression is a challenging task, because speckle noise is locally dependent in the form of multiplicative noise. It means that the pixel intensity is affected by the scatterers in the image resolution element due to speckle noise, which increases the difficulty of identifying features.

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Conclusion