摘要
本文研究在无需SAR图像先验知识条件下,基于多尺度自回归滑动平均MARMA模型的SAR图像压缩方法.该方法首先对SAR图像建立MARMA模型,依据MARMA模型对原始图像进行预测,然后对预测的残量进行数据压缩.将此方法用于实际SAR图像压缩,并将基于MARMA模型和多尺度自回归MAR模型的压缩结果与相应的JPEG结果进行比较和分析,说明基于MARMA模型的SAR图像压缩方法既能达到较高的压缩比,又能取得较好的保真度,是一种很有潜力的压缩方法.
In this paper, a new method based on muhiscale autoregressive moving average （MARMA） models is presented to compress SAR（Synthetic Aperture Radar）image. The method uses the multiscale representation as the cornerstone of the modeling process,and constructs the MARMA models of image.Thus we predict the initialized image data using these multiscale models, and the compression is subsequently achieved through coding the residual image. Unlike published methods, supervising segmentation for SAR image is not used in our compression processes. So the prior knowledge of segmentation is not required. Experimental results have proven that the proposed method achieves high compression radios with impressive image quality.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2005年第12期2111-2114,共4页
Acta Electronica Sinica
基金
国家自然科学基金(No.60375003)
航空基础科学基金(No.03I53059)
西北工业大学研究生创业种子基金(No.Z200566)
关键词
SAR图像压缩
多尺度自回归滑动平均模型
残差图像
SAR image compression
multiscale autoregressive moving average（MARMA） model
residual image
