Visual morphing is a class of techniques that deal with the metamorphosis of one image into another, which generates a series of smoothly continuous intermediate images between two given images. Over the past few years, a number of computable models of visual morphing have been developed. However, most of these models are based on the pixel domain. Little theoretical and computational work of visual morphing is based on the compressed domain. In this paper, two image morphing algorithms in the discrete cosine transform (DCT) domain are proposed. The first method is based on the feature-based method. Salient blocks and edge blocks as features are detected in the DCT domain first. Then feature correspondences are built manually. At last, a mapping function is constructed on two hierarchies. The second method is for the case that features are not distinct and feature correspondences can’t be built easily. A morphing method following the idea of fluid simulation is proposed. The experimental results have demonstrated the convenience, efficiency and accuracy of the proposed algorithm.