Inverse discrete cosine transform architecture exploiting sparseness and symmetry properties

In this paper, a novel architecture for two-dimensional (2-D) inverse discrete cosine transform (IDCT) is implemented using 90-nm CMOS technology. By exploiting the sparseness property of a 2-D discrete cosine transform (DCT) coefficient matrix and the even and odd symmetry properties of the basis vectors of the one-dimensional (1-D) DCT, the proposed architecture reduces computational complexity and increases a throughput rate effectively. First, we derive a recursion equation from the definition of the 2-D IDCT algorithm and use it to design an efficient 2-D IDCT architecture. The proposed architecture consisting of processing elements is suitable for very-large-scale-integration implementation due to its highly regular and scalable structure for 2-D N × N IDCT computations. Based on the derived recursion equation, we show how data flow for the outer products scaled by only nonzero 2-D DCT coefficients performs 2-D IDCT naturally with low complexities of the controller and the interconnection. The proposed architecture based on the recursion equation provides optimum balance in both hardware complexity and throughput rate when compared with other 2-D IDCT architectures.