HIGH-QUALITY IMAGE MAGNIFICATION APPLYING THE GERCHBERG-PAPOULIS ITERATIVE ALGORITHM WITH DCT

This paper proposes an image magnification method ''IM-GPDCT,'' which is an iterative application of the Gerchberg-Papoulis (GP) algorithm with the discrete cosine transform (DCT), and its performance is evaluated. Conventional image magnification by interpolation has a problem in that degradation of image quality is inevitable since essentially it is impossible to restore the spatial high-frequency components which are lost in the observation process. For this point, IM-GPDCT improves image quality of a magnified image by utilizing a concept to restore the spatial high-frequency components which are lost in the observation. IM-GPDCT uses the GP algorithm as the basic principle for extending the frequency band. The spatial high-frequency components are restored during the forward and inverse iterative transform process for the image by DCT, using two constraints that the spatial extent of an image is finite, and correct information is already known for the low-frequency components. The proposed method is compared to three conventional interpolation methods from the viewpoints of a restoration error and image quality. Restoration error performance results show that IM-GPDCT outperforms the interpolation methods from the viewpoint of the restoration error. Simulation results show also that the presented method improves the image quality of the magnified image by obtaining image sharpness, nonjagged edges and reproduction of the original texture.