FPGA Based Image Processing: A Comparative Study of Software-Centric and Hardware-Accelerated Approaches

This work compares two different approaches to image processing algorithm implementation in Zynq Zybo and Zedboard Field Programmable Gate Array (FPGA) boards. There are three main phases for the study, namely, Hardware-Accelerated Image Processing (HAIP), Software-Centric Image Processing (SCIP), and an in-depth analysis of their corresponding performance metrics. Image processing algorithms were implemented in the SCIP phase, exclusively using the Zynq Processing System (PS). On the other hand, the HAIP phase comprised creating distinct Intellectual Properties (IPs) for image processing tasks and integrating them with the Zynq PS through Direct Memory Access (DMA) and the Advanced eXtensible Interface (AXI) protocol.For all assessed techniques, HAIP considerably outperformed SCIP in terms of processing time, for different image sizes, across both Zynq Zybo and Zedboard. On the other hand, as SCIP is software-centric, it showed minimal resource utilization and lower power consumption than HAIP, which showed higher resource utilization and power consumption. However, both methods produced processed images that were similar, highlighting the stability and dependability of FPGA-based image processing implementations. A comparative analysis between Zynq Zybo and Zedboard reveals insights into how different FPGA architectures impact the performance and resource utilization of image processing implementations. This work offers insights into the trade-offs between hardware-accelerated and software-centric approaches to image processing on FPGA platforms, guiding future design decisions for practical uses.