Abstract
Synthetic Aperture Radar (SAR) image compression is important in image transmission and archiving. In this paper, SAR image compression using embedded zerotree wavelets algorithm, based on discrete wavelet transform (DWT), is researched. Aiming at special characteristics of SAR image such as speckle noise, the author added a denoise step in the flow of compression, trying to do some meaningful attempt in SAR image compression. Experiments carried out show that the improvement can reduce the speckle noise and improve the computation precision and time.
Key words Synthetic Aperture Radar, discrete wavelet transform, Image Embedded Compression, image denoise
I. INTRODUCTION
Synthetic aperture radar (SAR) is a very efficient instrument for obtaining a better understanding of the environment. SAR image products are very important and useful for remote sensing applications because they can be acquired independent of time or day or weather conditions and because their characteristics (wavelength, polarisation, observation angle) can be chosen in function of the phenomenon under investigation. So SAR image compression is important in image transmission and archiving. Due to the high entropy of SAR raw data, conventional compression techniques fail to ensure acceptable performances, in that lossless ones do not in fact succeed to compress, while general purpose lossy ones (e.g. JPEG) provide some compression degree only at the price of unacceptable image quality degradation[1]. Furthermore the presence of speckle noise in SAR images limits the visual interpretation of scenes because it obscures the content. In order to get reliable data interpretation and quantitative spots measurements, it is recommended to applying speckle filtering schemes in SAR image compression.
In this paper, SAR image compression using embedded zerotree wavelets algorithm, based on discrete wavelet transform (DWT), is researched. Aiming at special characteristics of SAR imagery such as speckle noise, the author added a denoise step in the flow of compression, trying to do some meaningful attempt in SAR image compression. Experiments carried out show that the improvement can reduce the speckle noise and improve the computation precision and time.
The organization of this paper is as follows. In section Ⅱ, the proposed flow of SAR image compression is presented, where the three stages of it are discussed respectively. Finally, we give the experimental results in section Ⅲ and conclusions in section Ⅳ.
Ⅱ. SAR IMAGE EMBEDDED COMPRESSION
Although speckle noise is an inherent nature of SAR images, the presence of speckle noise in SAR images limits the visual interpretation of scenes. So far speckle noise have not used to help the interpretation of SAR despite there may be some information in speckle noise. The author had done some experiments using conventional compression techniques alone in SAR image compression. These experiments showed that conventional compression techniques failed to ensure acceptable performances and couldn’t weaken the phenomenon of speckle noise.
In this paper, the author adopted EZW algorithm in SAR image compression and added a denoise step before encoding.


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