Hardware Architectures for Real Time Image Processing

Dear Colleagues,

The development of hardware architectures for real-time image processing is an important requirement when dealing with critical applications where data must be processed in a restricted timeframe. Moreover, it is an interdisciplinary field that gives support to a wide variety of disciplines, such as electronic engineering, computer science, industrial control, physics, mathematics, biology, food quality assessment, medicine, etc. Although these circumstances arise in several applications, and several solutions have been proposed in the past, the large amount of data per unit of time currently provided by image sensors supposes a major challenge for feasible hardware implementations. Not only have the frame-rates and the resolution of the images increased, but additionally, some image modalities incorporate spectral information, depth information, contextual information, metadata, etc., making the implementation requirements even more stringent. In addition to time processing, many systems must meet constraints on weight, size, power or cost, resulting in exhaustive and time-prohibitive design-space explorations. To cope with these complex situations, several solutions have been addressed, including (but not limited) compressive sensing for data reduction, multimodal image and video compression, efficient high-speed memory management at different levels for high-bandwidth communications, fast interfaces for data transactions, high-level synthesis methodologies for high-performance implementations, heterogeneous implementations combining ASICS, FPGAs, GPUs, manycore processors, etc. This Special Issue on “Hardware Architectures for Real-Time Image Processing” aims to include different implementation solutions for real-time image processing, provided that such solutions suppose a significant scientific contribution in the field.

Dr. Gustavo Marrero Callico
Dr. Himar Fabelo
Dr. Lucana Santos
Guest Editors

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