In this paper, we propose a VLSI architecture that performs the line-based discrete wavelet transform （DWT） using a lifting scheme. The architecture consists of row processors, column processors, an intermediate buf...In this paper, we propose a VLSI architecture that performs the line-based discrete wavelet transform （DWT） using a lifting scheme. The architecture consists of row processors, column processors, an intermediate buffer and a control module. Row processor and Column processor work as the horizontal and vertical filters respectively. Intermediate buffer is composed of five FIFOs to store temporary results of horizontal filter. Control module schedules the output order to external memory. Compared with existing ones, the presented architecture parallelizes all levels of wavelet transform to compute multilevel DWT within one image transmission time, and uses no external but one intermediate buffer to store several line results of horizontal filtering, which decreases resource required significantly and reduces memory efficiently. This architecture is suitable for various real-time image/video applications.展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos.60532060 and 60507012.
文摘In this paper, we propose a VLSI architecture that performs the line-based discrete wavelet transform （DWT） using a lifting scheme. The architecture consists of row processors, column processors, an intermediate buffer and a control module. Row processor and Column processor work as the horizontal and vertical filters respectively. Intermediate buffer is composed of five FIFOs to store temporary results of horizontal filter. Control module schedules the output order to external memory. Compared with existing ones, the presented architecture parallelizes all levels of wavelet transform to compute multilevel DWT within one image transmission time, and uses no external but one intermediate buffer to store several line results of horizontal filtering, which decreases resource required significantly and reduces memory efficiently. This architecture is suitable for various real-time image/video applications.
