【摘要】 目前常用的无损图像压缩方法都是利用相邻数据组合除去数据中存在的相关性。既然局部或相邻像素间存在一定的灰色关联度 [1 ] ,而非线性灰色模型又可以从邻近像素中提取灰色关联 ,因此提出了一种快速灰色预测模型(FGMP) ,并构建非线性预测模式 ,可以在灰度图像无损压缩中实现预测误差编码。运用该算法进行了图像压缩 ,并得出了一些结论更多还原

【Abstract】 The most used methods for lossless image compression are to remove the data redundancy by using the combination of its neighbors The local or neighboring pixels have some gray relationship existence , so we proposed one predictive algorithm: Fast gray model predictor (FGMP), to construct nonlinear predictive schemes, which can implement the predictive error coding in a lossless compression of gray scale images and has higher compression rate更多还原