遥感图象是难的因为他们的富有的质地,完成高压缩比。由在图象压缩上分析小浪性质的影响,这篇论文建议小浪构造规则并且造一个新双性人有参数的直角的小浪构造模型。模型参数被使用遗传算法并且作为优化目标功能采用精力压缩优化。另外,以便解决联机建设的计算复杂性问题,根据在这篇论文建议的图象分类规则,我们为图象的不同的班构造小浪并且实现快自适应子波选择算法(FAWS ) 。试验性的结果证明 FAWS 的小浪库比 Daubechies9/7 获得更好的压缩性能。电子增补材料这篇文章(doi:10.1007/s11390-007-9086-7 ) 的联机版本包含增补材料,它对授权用户可得到。
Remote sensing images are hard to achieve high compression ratio because of their rich texture. By analyzing the influence of wavelet properties on image compression, this paper proposes wavelet construction rules and builds a new biorthogonal wavelet construction model with parameters. The model parameters are optimized by using genetic algorithm and adopting energy compaction as the optimization object function. In addition, in order to resolve the computation complexity problem of online construction, according to the image classification rule proposed in this paper we construct wavelets for different classes of images and implement the fast adaptive wavelet selection algorithm (FAWS). Experimental results show wavelet bases of FAWS gain better compression performance than Daubechies9/7.