IMAGE-RESTORATION BASED ON A WIENER FILTERING TECHNIQUE USING DISCRETE COSINE TRANSFORM

This paper proposes a Wiener filtering restoration technique for a deg raded image using the discrete cosine transform (DCT). The principle o f the method is based on the property that the convolution that repres ents the degradation corresponds to the multiplication in the DCT tran sform domain. Using DCT, the condition assumed for the signal becomes more practical compared to conventional Wiener filtering using the dis crete Fourier transform (DFT). In other words, instead of the periodic boundary condition in DFT, the even symmetry of the boundary conditio n is assumed. Because of this property, the generation of the false fr equency component is suppressed and a better restoration is obtained. The DCT Wiener filtering is formulated using the matrix-vector represe ntation. It is shown first that the matrices representing the image mo del and the degradation model are diagonalized by DCT. Then, it is sho wn that the filter gain is represented in terms of the eigenvalues of those matrices. As degradations, a uniform one- and two-dimensional bl ur, as well as a two-dimensional Gaussian blur, are considered. Throug h computer experiment using simulated and actual degraded images, the effectiveness of the proposed method is demonstrated. Then, the block partitioning is applied, and the adaptive processing considering the n onuniformity of the image is presented.