I'm trying to implement a feature based image registration algorithm. From my observation, description of each feature point (key point) is required before the matching operation. Is it mandatory to describe the features, if yes, why?
Kindly help me...
Short answer: Yes, it is mandatory to describe the keypoints.
Let me elaborate: a keypoint detector usually only extracts "interesting" points in the image (usually corner-like structures, examples include the Harris detector). The output of keypoint detectors is usually only a list of pixel locations corresponding to "interesting" locations. In order to match these keypoints to the keypoints in the image you want to register, you need to describe the keypoints by some vector. The simplest description my be the pixel's color and location, or the color histogram in a local neigborhood. However, more sophisticated keypoint descriptors like SIFT also use gradient information (mangitude, direction) and usually aim to introduce some invariances (e.g. to scale and rotation). Given a feature vector (or descriptor) for each keypoint, the keypoints can be matched using an arbitrary distance in the corresponding vector space (e.g. Euclidean). In this sense, computing an appropriate vector representation for each keypoint is referred to as "describing the keypoint". Without a description, you cannot match the keypoints. Therefore, a (good) descriptor is necessary (and crucial) for image registration.
Note, however, that not all image registration techniques are based on extracting or matchign keypoints. See the Wikipedia article to get a short overview about different approaches to image registration.
