Parallel, pipelined and folded architectures for computation of 1-D and 2-D DCT in image and video codec

Several parallel, pipelined and folded architectures with different throughput rates are presented for computation of DCT, one of the fundamental operations in image/video coding. This paper begins with a new decomposition algorithm for the 1-D DCT coefficient matrix. Then the 2-D DCT problem is converted into the corresponding 1-D counterpart through a regular index mapping technique. Afterward, depending on the trade-off between hardware complexity and speed performance, the derived decomposition algorithm is transformed into different parallel-pipelined and folded architectures that realize the butterfly operations and the post-processing operations. Compared to other DCT processor, our proposed parallel-pipelined architectures, without any intermediate transpose memory, have the features of modularity, regularity, locality, scalability, and pipelinability, with arithmetic hardware cost proportional to the logarithm of the transform length.