Image Processing Hardware Acceleration—A Review of Operations Involved and Current Hardware Approaches
Costin-Emanuel Vasile, A. Ulmamei, Călin Bîră
Abstract
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.
Topics & Concepts
Hardware accelerationField-programmable gate arrayComputer scienceApplication-specific integrated circuitKey (lock)AccelerationComputer hardwareEmbedded systemImage processingImplementationComputer architectureReconfigurable computingImage (mathematics)Artificial intelligenceOperating systemClassical mechanicsPhysicsProgramming languageCCD and CMOS Imaging SensorsAdvanced Memory and Neural ComputingAdvanced Neural Network Applications