1. A method of sparse representation of contents of high-resolution video images which supports content editing and propagation, characterized in that the specific steps thereof comprise: inputting the original high-resolution images or videos and summarizing the characteristic information of their pixels and remove the pixels of same characteristics; acquiring the highly sparse samples of the original images or videos through the sparse representation technique; utilizing 11 basic colors to classify the pixels of the original images or videos into 11 types in terms of the Euclidean distance between the pixel color and each of 11 basic colors; extracting separately the sparse samples from each of 11 types of pixels which can represent its nature feature and then combining 11 sparse samples acquired into the final sparse sample which contains the nature features of all the pixels of the original images or videos; reconstructing each pixel of the input images or videos through a small number of the original sparse samples to calculate the coefficient of reconstruction; the number of the selected sparse samples to reconstruct each pixel is self-adaptive with a principle that a minimum quantity of samples are used to reconstruct the original pixel and the calculated reconstruction coefficient establishes a linear relationship between the input pixel and the original sparse samples; editing and propagating the original sparse samples to yield the result of sparse samples; the editing and propagating of the original sparse samples comprises three methods as follows: interactive recoloring of video object, conversion of color style of video scene and seamless integration between object and scene; generating the result of all the pixels according to the result of sparse samples and the reconstruction coefficient so as to yield the result of high-resolution images or videos.