Super resolution refers to obtaining an image that has a higher resolution than of image sensor used in capturing the image. what are the fundamental principles on which domain methods for the reconstruction of super-resolution images are based?

It is based upon the combination of non-repetitive information contained by multiple Low Resolution images. The basic principle of Super Resolution is a construction of High Resolution images from several Low Resolution images, thereby increasing the high frequency components. There are two approaches to increasing the resolution of an image. The first approach is called patch redundancy technique where each Low Resolution patch is replaced by its corresponding High Resolution patch. The second approach is enhancing the edges of those objects present in your image.