| 1. | Complex spectral resolution
复谱分解 |
| 2. | At the same time , hyperspectral images with much higher spectral resolution have been made available with the invention of imaging spectrometer
而成像光谱仪的问世使获取高光谱分辨率的高光谱图像数据成为可能。 |
| 3. | Compared to multi - spectral image , hyperspectral image is high spectral resolution , narrow band , and has many bands . it can distinguish targets with reliability
与多光谱图像相比,高光谱图像光谱波段数目多、光谱分辨率高、波段宽度窄,能够以较高的可信度区分和辨识地物目标。 |
| 4. | The performance of high spectral resolution makes it suitable for the detection of human - made targets surrounded by natural environment background . therefore , it becomes more and more popular
高光谱图象良好的光谱诊断能力使得它非常适合对照自然背景发现人工目标,因此越来越受到各国的重视。 |
| 5. | While spectral resolution increases as slit width decreases , a narrow input slit greatly limits the light throughput and as a result reduces the signal - to - noise ratio of the measurement
当光谱分辨率增加的时候，狭缝宽度就会降低；而一个窄的狭缝宽度将会对光线的吞吐量产生极大的限制，并导致降低了测量的信噪比。 |
| 6. | However , such a high spectral resolution is on the expense of even huge data volume , which brings new challenges to the current techniques for storage and transmission . therefore , it is necessary to compress these large data sets
但是,高光谱图像较高的光谱分辨率的获得是以其巨大的数据量作为代价的,这给高光谱图像的存储、传输和处理都带来了困难。 |
| 7. | Modern spectra1 ana1ysis techno1ogy is called the high resolution spectral analysi s technology because of its advantage wh ich have more hi gh spectral resolution ratio and overcome the di sadvantage of the classical spectral analys is
现代谱分析技术是针对经典谱分析的缺点发展起来的。现代谱分析技术的主要优点是能得到比较高的谱分辨率，所以这一类谱分析技术又叫高分辨谱分析技术。 |
| 8. | Mms - based instruments are ideal for measuring weak , scattering and diffuse sources and samples because the spectrometer can collect and process far more light through its wide area aperture , without affecting spectral resolution
基于mms技术的设备非常适合测量测量难以测量的、散射的发散源以及样品，因为通过一个大口径编码光阑，这种光谱仪就能够集聚并处理更多的光线，而不会影响光谱分辨率。 |
| 9. | The high dimensional multispectral data , which features high spectral resolution , high spatial resolution , and large dynamic range , have provided luxuriant information about earth surface for people . because the number of training samples is limited and data dimension is high , the performance of traditional pattern classification algorithms is deteriorated
高维多光谱数据分类中，由于训练样本非常有限、数据维数很高，以经验风险最小化为归纳原则的传统模式识别方法通常难以取得很好的结果。 |
