Image Processing Hardware Acceleration-A Review of Operations Involved and Current Hardware Approaches.

This review provides an in-depth analysis of current hardware acceleration approaches for image processing and neural network inference, focusing on key operations involved in these applications and the hardware platforms used to deploy them. We examine various solutions, including traditional CPU-GPU systems, custom ASIC designs, and FPGA implementations, while also considering emerging low-power, resource-constrained devices.