摘要
目前多光谱成像已被广泛应用在遥感领域中,但巨量的多光谱图像数据导致存储和传输的困难,这就需要对多光谱图像数据进行高效的压缩。该文提出了一种新的多光谱图像压缩算法(KLT/WT-3DSPECK),首先利用二维小波变换(2DWT)去除多光谱图像的空间相关冗余,然后利用Karhunen-Loeve变换(KLT)减少频域的相关性,最后对变换后的系数利用改进的三维集合块分裂算法(3DSPECK)进行编码。根据变换后子带能量分布的特点,提出了新的3D八度音符分裂方法(octavepartitioning)和改进的集合零块分裂算法。为了加速本文算法和优化嵌入码流的率失真性能,还给出了一种零块优化排序的快速算法。对两组多光谱和超光谱图像的测试表明,该算法不仅明显优于KLT/WT-3DSPIHT算法,也远优于基于3D小波变换的AT-3DSPIHT和3DSPECK等算法,同时该算法还支持图像的渐进传输。
Multispectral imaging has been widely used in the field of remote sensing. The storage and transmission of large volumes of multispectral data have become significant concerns. Therefore efficient compression is required for storage and transmission. This paper proposes a new multispectral image data compression algorithm （KLT/WT3DSPECK）. First, a 2D wavelet transform is applied to reduce the spatial redundancies. Next a Karhunen-Loeve Transform （KLT） is used to remove the correlation between adjacent spectral bands. Finally a modified 3DSPECK method is proposed and is used to code the transformed coefficients. According to the distribution of energy of the transformed coefficients, a novel 3D octave partitioning scheme and an improved set partitioning zeroblock method are presented. To accelerate the speed and optimize the rate-distortion performance of the embedded bit stream, a fast algorithm of the optimal zeroblock sorting is given. Numerical experiments on two sample multispectral images show that the proposed KLT/WT-3DSPECK algorithm outperforms either the KLT/WT-3DSPIHT algorithm or the 3DWT-based AT-3DSPIHT and 3DSPECK algorithms. Besides having high performance, the KLT/WT-3DSPECK algorithm support progressive transmission.
出处
《电子与信息学报》
EI
CSCD
北大核心
2005年第8期1244-1248,共5页
Journal of Electronics & Information Technology
基金
国家自然科学基金(60371020)资助课题
