| 1. | Maximum likelihood classification
最大似然分类 |
| 2. | Many classification methods exist including nearest - to - means , maximum likelihood classification method , bayes classification method , and neural network classification
图象分类之理论与方法甚多，包括最近均值法、最大概似法、具氏分类法等。 |
| 3. | Many classification methods exist including nearest - to - means , maximum likelihood classification method , bayes classification method , and neural network classification
影像分类之理论与方法甚多，包括最近均值法、最大概似法、具氏分类法等。 |
| 4. | Based on two satellite images from landsat tm / etm + , land use types are measured through the method of maximum likelihood classification . land use change areas are determined and extracted by using post - classification comparison . for further study on the time and spatial characteristic of land use change in longhai county from 1989 to 2000 , the mathematical methodologies are established
因此本文利用1989年和2000年两期的landsattm / etm遥感图像，采用最大似然法的监督分类完成对两个时相各土地利用类型的测量，基于分类后比较法发现和提取土地利用变化信息。 |
| 5. | Based on the optimum theory of multi light spectrum hands and the analysis of the inter relation of various hands of the pictures of white cells , a new classification method a great improvement on the traditional maximum likelihood classification - has been suggested which can classify the most effective parts of the hands of the white cell pictures
摘要基于多光谱波段的优化理论，在白细胞图像各波段间相关性分析的基础上，对传统最大似然分类法进行改进，提出一种对白细胞图像选择最有效部分波段进行识别的分类方法。 |
| 6. | By combining bayesian principles and other priori knowledge , the method has improved the degree of accuracy of classification and overcome shortcomings of immense data quantity , complexity of calculation and slow speed of recognition which exist in traditional maximum likelihood classification in recognizing pictures
该方法通过贝叶斯理论与其他先验知识进行融合，提高了分类准确度，克服了传统最大似然分类法在图像识别过程中具有的数据量庞大、计算程度繁冗和识别速度慢等缺点。 |
| 7. | The results show that the maximum likelihood classification based on variogram texture and spectral bands can perfectly define the grades of beach sandy land and inner desertification , and the maximal classification precision comes up to 92 . 4 % , which proves that geostatistical texture is effective in the application of desertification monitoring
结果表明，运用变异函数纹理结合光谱波段的最大似然分类方法能够很好地界定海滩沙地和内陆荒漠地的等级，最高分类精度达到92 . 4 % ，证明了基于地质统计学的影像纹理在实现该地区遥感荒漠化监测方面的有效性。 |
