A Non-Expansive Convolution for Nonlinear-Phase Paraunitary Filter Banks and Its Application to Image Coding
Yuichi Tanaka, Akie Ochi, Masaaki Ikehara · 2006
This paper proposes a new non-expansive convolution for nonlinear-phase paraunitary filter banks (NLPPUFBs). First, we present that any NLPPUFBs can be implemented by connecting several block transforms. Next, we show a signal extension method at the analysis bank by exploiting the characteristics of that structure. Furthermore, we prove that the signal can be reconstructed at the synthesis bank without any redundant signals. Finally, we apply the proposed extension to image coding to validate our method