Sci. Applications Int. Corp., San Diego, CA.
IEEE Trans Image Process. 1997;6(1):143-56. doi: 10.1109/83.552103.
Multispectral or hyperspectral sensors can facilitate automatic target detection and recognition in clutter since natural clutter from vegetation is characterized by a grey body, and man-made objects, compared with blackbody radiators, emit radiation more strongly at some wavelengths. Various types of data fusion of the spectral-spatial features contained in multiband imagery developed for detecting and recognizing low-contrast targets in clutter appear to have a common framework. A generalized hypothesis test on the observed data is formulated by partitioning the received bands into two groups. In one group, targets exhibit substantial coloring in their signatures but behave either like grey bodies or emit negligible radiant energy in the other group. This general observation about the data generalizes the data models used previously. A unified framework for these problems, which utilizes a maximum likelihood ratio approach to detection, is presented. Within this framework, a performance evaluation and a comparison of the various types of multiband detectors are conducted by finding the gain of the SNR needed for detection as well as the gain required for separability between the target classes used for recognition. Certain multiband detectors become special cases in this framework. The incremental gains in SNR and separability obtained by using what are called target-feature bands plus clutter-reference bands are studied. Certain essential parameters are defined that effect the gains in SNR and target separability.
多光谱或高光谱传感器可以促进杂波中自动目标检测和识别，因为自然杂波的植被具有灰色物体的特征，而与黑体辐射器相比，人造物体在某些波长下辐射更强。为了检测和识别杂波中的低对比度目标，开发了多波段图像的光谱-空间特征的各种类型的数据融合，它们似乎具有共同的框架。通过将接收到的波段分成两组，对观测数据进行广义假设检验。在一组中，目标在其特征中表现出明显的颜色，但在另一组中要么表现得像灰色物体，要么发射出可忽略不计的辐射能。这一关于数据的一般观察结果推广了以前使用的数据模型。提出了一个用于这些问题的统一框架，该框架利用最大似然比方法进行检测。在这个框架内，通过找到检测所需的 SNR 增益以及用于识别的目标类之间的可分离性所需的增益，对各种类型的多波段检测器进行了性能评估和比较。某些多波段检测器在这个框架内成为特例。研究了使用所谓的目标特征波段加杂波参考波段获得的 SNR 和可分离性的增量增益。定义了某些影响 SNR 和目标可分离性增益的基本参数。
