方向自适应提升小波在遥感图像中的研究

针对于遥感图像纹理复杂的特点，提出了一种利用自适应方向提升方案的遥感图像压缩编码新方法。传统的提升方法主要在垂直和水平方向上进行，从而降低垂直和水平方向上像素的相关性；与传统的提升方法不同，基于自适应方向提升的方法充分利用了图像其他纹理方向的相关性来进一步提高预测的精度，从而降低高频部分的能量值。该算法首先利用自适应方向提升的方法对遥感图像进行多尺度快速整数小波变换，然后采用子带位平面编码算法来实现遥感图像的高效压缩编码。实验结果表明，对一般遥感图像，该算法在高倍率压缩的情况下要优于目前的JPEG2000算法。

Research on Remote Sensing Image Compression Using Orientation-adaptive Lifting Wavelet

This paper addresses the problem of image compression in remote sensing applications. Compared with other static images, remote-sensing images are characterized with complex textures and weak local correlation. Most of current wavelet-based algorithms of image compression have not taken this into account, in which the predictions are always performed in the horizontal or vertical directions. In order to further improve coding efficiency, an efficient remote sensing image coding algorithm based on orientation-adaptive lifting wavelet(OALW) is proposed. First, the OALW is applied to the image at the direction where the pixels have a strong correlation, rather than at the horizontal or vertical orientation. Compression is then achieved by using a subband-bit-plane encoding method. In the experiments, two satellite images are selected to test the performance of the algorithm. Experimental results illustrate that it provides higher performance than JPEG2000 in low-bits compression.