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Research And Implementation Of Speckle Denoising Algorithm Based On Curvelet Transform In SAR Image

Posted on:2006-05-30Degree:MasterType:Thesis
Country:ChinaCandidate:T HeFull Text:PDF
GTID:2168360152989619Subject:Circuits and Systems
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Synthetic Aperture Radar (SAR) is a kind of high resolution imaging radar, which has been developed since World War Ⅱ. High-resolution radar image can be obtained under all weather, day-and-night and long distance conditions, so it is of high value in military and civil applications. Now research of speckle denoising algorithm in SAR image gradually becomes the hot topic of study. Supported by the Foundation Research Project of Jiangsu Province (The Natural Science Fund N0.BK2001047) "Research On SAR Image Evaluation", we apply a multiscale transform— Curvelet transform which has more better performance in edge detection to speckle denoising in SAR image, then research on the implementation of this algorithm on DSP parallel system and the FPGA simulation of wavelet as the main part in this algorithm. In the preface to this article, first, the basic purpose and significance of speckle smoothing for SAR images are introduced briefly. Secondly, we look back on the history of the speckle reduction and image evaluation. And finally, the principal contribution of this dissertation is summarized here. In chapter 2 we particularly describe the mechanism of speckle forming, discuss the noise model and the statistical characteristic of SAR image, introduce the main parameters for evaluating the quality of SAR image. In chapter 3 we research on the application of Curvelet speckle denoising in SAR image, then propose an improved algorithm which it hold the more struct information by applying the morphology filter to the denoised image. In chapter 4 several projects of Curvelet realized based on the DSP parallel system are discussed, then we research on the implementation of the soft (hard) threshold Curvelet algorithm on SHARC parallel process system. In chapter 5 we research on the simulation of wavelet FPGA, and this work estabilish a right foundation for the next step –Curvelet transform hardware realization. In the end, conclusions are made and the possible future work is explained.
Keywords/Search Tags:Synthetic Aperture Radar (SAR), speckle denoising, Curvelet transform, Ridgelet transform, Radon transform, SHARC, FPGA
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