Applcation of Multiscale Edge Detection to Speckle Reduction of SAR images
Siriporn Dachasilaruk, Yuttapong Rangsanser, and Punya Thitimajshima
Department of Telecommunications Engineering,
Faculty of Engineering
King Mongkut's Institute of Technology Ladkraband, Bangkok 10520
Tel: (66 2) 326-9967, Fax (66 2) 326-9086
Thailand
E-mail :kryuttha@kmitl.ac.th,
ktpunya@kmitl.ac.th
Abstract
This paper describes a method of speckle reduction in synthetic aperture radar (SAR) images based on multiscale edge detection and wavelet thresholding. The edge regions are detected in each scale. The wavelet decomposition is performed on the logarithm of the image gray levels. A threshold value is estimated according to the noise variance in each subband and used for soft-thresholding. The image gray levels. A threshold value is estimated according to the noise variance in each subband and used for soft-thresholding. The image is then obtained by reconstruction from the thresholded coefficients, and the exponential function of this image gives the final filtered image. Experimental results on a JERS-1/SAR image showed that the proposed method provided a significant noise removal and preserves the sharp feature of the image.
1.Introduction
Synthetic aperture radar (SAR) technology has resulted in marked improvements in the spatial resolution images when observing a ground scene from aircraft or satellites and it can be used to estimate also features like the dampness of soil, the thickness of the forest, or the roughness of the sea. Nevertheless, SAR images are contaminated by multiplicative noise, resulted from the necessity of creating the image with coherent radiation. When an object is illuminated by of the incident radiation, the wave reflected from such a surface consists of contributions from many independent scattering point. Inference of these dephased but coherent waves result in the granular pattern known as "speckle". Therefore, speckle reduction is an important and essential procedure in most target detection and recognition systems.
Typical noise-non-edging methods are not well suited to preserve edge structure in speckled images. Classical operators are based on the local variance statistics (Lee, 1986; Burrus. 1987) and the multiresolution wavelet technique, the multiscale edge representation (MER) have been proposed as well (Rogers, 1998). Recently a novel approach for noise reduction due to (Donoho, 1995) has been established. It employs thresholding in wavelet domain. Moreover the same method can be used in a wide variety of related problems such as data compression and of SAR images such as in our previous work (Thitimajshima. 1998). An improvement is proposed in this paper, by applying the thresholding only to the wavelet coefficients that correspond to non-edge regions, and keeping edge-like regions intact.
The propsed method is described in Section 2, including the multiscale edge detection and wavelet thresholding techniques. Section 3 present two quantitative measures for evaluation of presented. Finally, section 5 provides a conclusion of the paper.
2.The Proposed Method
The basis of our proposed method, we first perform a segmentation to identify the edge regions based on multiscale edge detection, or less exactly, to identify the non-edge regions of the images. The speckle noise is the most observable in non-edge regions of SAR images. Then the wavelet decomposition is performed on the logarithm of the image gray levels. We find a simple and very effective way to estimate threshold value by taking the standard deviation in each highpass band and used for the soft-thresholding operation except the edge regions, in all highpass bands. The despeckled logarithmic image is then obtained by reconstruction from the thresholded coefficients, as illustration in Figure 1.
Figure 1: diagram of the proposed method.
