Abstract: As one kind of typical signals,an image can theoretically be composed of a series of basic signals.In order to find a set of basic signals to reconstruct images,a method for obtaining basis images based on feature extraction and reconstructing images from them is proposed.It makes possible to obtain the basis images from any set of images and to reconstruct images from the obtained ones because it is content-independent.The algorithm flow of extracting a series of basis images from the training set of images by feature extraction algorithm is described.The system of reconstructing the original image from the proJection coefficient and basis images by proJecting the set of test images into the space formed by the k basis images is developed.The experimental results show that,by controlling the number of basis images,the error and quality of reconstucted images can achieve higher requirement,and the method for basis images extraction and image reconstruction is content-independent.At the same time,this method plays an important role in the understanding of abstract features of images and the deep neural network.

Key words: Basis image, Content-independent, Feature extraction, Feature vectors, Image reconstruction