基于感兴趣区域的海洋卫星遥感图像压缩算法

针对海洋监视卫星遥感图像的特点,提出了一种基于感兴趣区域的自适应遥感图像近无损压缩算法。该算法利用红-黑小波提升方法检测出目标的边缘,采用阈值法将目标和背景分割,使用外接矩形来描述目标,从而自动确定感兴趣区域。感兴趣区域采用Rice无损熵编码方法,背景区域采用比特平面编码的有损压缩方法。实验结果表明,该算法能有效地划分感兴趣区域,其压缩比较无损压缩有了很大提高,目标无失真,整幅图像的峰值信噪比都在40dB以上。算法的计算复杂度较低,易于硬件实现,而且还具有自适应性和数据包独立的优点,适合于海洋监视卫星遥感图像近无损压缩应用。

A compression algorithm of remote sensing image based on Region of Interest for ocean surveillance satellite applications

According to the characteristics of the remote sensing images from ocean surveillance satellite,an adaptive near-lossless compression algorithm based on ROI(Region of Interest) is proposed.The object's edge is detected by redblack wavelet lifting,the object and background are segmentalized by threshold, enclosing rectangle is used to depict the object,and ROI is automatically defined.Rice lossless entropy encoder is used for ROI,and bit plane encoder for background region.Experiments show that the algorithm could segmentalize the ROI effectively,CR(compression ratio)is higher than lossless compression,the object keep original fidelity,PSNR(Peak Signal to Noise Ratio) of the whole image is higher than 40dB.The algorithm possesses low complexity and is easy to be implemented in hardware.Moreover,it has the merits of adaptability,and independent data packet.So the algorithm can adapt to ocean surveillance satellite's near-lossless compression applications.