The invention relates to a method for detecting a computer generated image and a natural image based on wavelet transformation, which belongs to the technical field of image detection. The method comprises the following steps: firstly, performing color channel transformation to an image to be detected, transforming a RGB color image into an HSV color image; secondly, transforming all channels of the image further to obtain a multi-dimensional eigenvector including statistic matrix characteristics and high-frequency filter characteristics; thirdly, extracting characteristics by utilizing characteristics of the computer generated image and the natural images; fourthly, rapidly judging the truth of the image by a support vector machine (SVM), and detecting whether the image is the computer generated image or the natural image. The invention adopts a technology of combining the statistic matrix characteristics and the high-frequency filter characteristics, and has the characteristics of high precision, complete characteristics extraction, complete detection and the like, thereby greatly improving the detection precision.