1. A method for object detection in remotely-sensed images, the method comprising: identifying a first domain within a remotely-sensed image, wherein the first domain comprises textural features and spectral features; training a first classifier to detect a first object within the image based on a textural relationship between the textural features within the first domain; training a second classifier to detect the first object based on: the textural relationships within the first domain; and a spectral relationship between the spectral features within the first domain; learning a classifier relationship between the trained first classifier and the trained second classifier; training an object detector to detect at least one object based on the learned classifier relationship in the first domain; detecting the at least one object within a second domain using the trained object detector, wherein the second domain comprises textural and spectral features; comparing the detection of the at least one object in the first domain to the detection of the at least one object detected in the second domain; modifying the object detector based on the comparison between the detection of the at least one object in the first domain and the detection of the at least one object in the second domain; and detecting one or more objects in an additional domain with the modified optimal fast object detector.
1. A method for object detection in remotely-sensed images, the method comprising: identifying a first domain within a remotely-sensed image, wherein the first domain comprises textural features and spectral features; training a first classifier to detect a first object within the image based on a textural relationship between the textural features within the first domain; training a second classifier to detect the first object based on: the textural relationships within the first domain; and a spectral relationship between the spectral features within the first domain; learning a classifier relationship between the trained first classifier and the trained second classifier; training an object detector to detect at least one object based on the learned classifier relationship in the first domain; detecting the at least one object within a second domain using the trained object detector, wherein the second domain comprises textural and spectral features; comparing the detection of the at least one object in the first domain to the detection of the at least one object detected in the second domain; modifying the object detector based on the comparison between the detection of the at least one object in the first domain and the detection of the at least one object in the second domain; and detecting one or more objects in an additional domain with the modified optimal fast object detector. 9. The method of claim 1 , wherein the first classifier is a linear classifier.