Block-based frequency scalable technique for efficient hierarchical coding

In this paper, we propose a block-based frequency scalable technique for efficient hierarchical coding. The proposed technique divides an image into its multiple resolution versions, based on the spectral properties of discrete cosine transform (DCT) kernels. We present that spectral decomposition, downsampling, and DCT operations are performed effectively over input DCT coefficients of one-dimensional (1-D) and two-dimensional (2-D) signals by using the proposed transform matrices. The proposed image coder is observed to reduce the computational complexity and the memory buffer size with a higher peak signal-to-noise ratio (PSNR), when compared with the traditional hierarchical image coder. In addition, the proposed architecture can preserve compatibility easily with the previous DCT-based image coder.