Block based texture synthesis algorithms have shown better results than others as they help to preserve the global
structure. Previous research has proposed several approaches in the pixel domain, but little effort has been taken in the
synthesis of texture in a multiresolution domain. We propose a multiresolution framework in which coefficient-blocks of
the spatio-frequency components of the input texture are efficiently stitched together to form the corresponding
components of the output texture. We propose two algorithms to this effect. In the first, we use a constant block size
throughout the algorithm. In the second, we adaptively split blocks so as to use the largest possible block size in order to
preserve the global structure, while maintaining the mismatched error of the overlapped boundaries below a certain error
tolerance. Special consideration is given to minimization of the computational cost, throughout the algorithm designs.
We show that the adaptation of the multiresolution approach results in a fast, cost-effective, flexible texture synthesis
algorithm that is capable of being used in modern, bandwidth-adaptive, real-time imaging applications. A collection of
regular and stochastic test textures is used to prove the effectiveness of the proposed algorithm
