This paper presents a real-time image enhancement technique for gastric endoscopy, which is based on the variational approach of the Retinex theory. In order to efficiently reduce the computational cost required for image enhancement, processing layers and repeat counts of iterations are determined in accordance with software evaluation result, and as for processing architecture, the pipelining architecture can handle high resolution pictures in real-time. To show its potential, performance comparison between with and without the proposed image enhancement technique is shown using several video images obtained by endoscopy for different parts of digestive organ.

Heart rate (HR) sensing during exercise is essential for medical, healthcare and sport physiological purposes. Photo-Plethysmo-Graphy (PPG) is a simple and non-invasive technique for HR sensing, but it is highly sensitive to motion artifact. This paper proposes a cancellation technique of motion artifact in PPG-based HR sensing for a man during exercise. The canceller is equipped with two sensors; one is a normal PPG sensor where an LED/Photo-Detector (PD) contacts the skin to detect Blood Volume Pulse (BVP) (+motion artifact) and the other is a motion artifact sensor where an LED/PD does not contact the skin to detect only motion artifact. Experimental results show that the proposed technique, which is implemented in adaptive algorithms, can sense HR correctly by cancelling motion artifact induced by exercises such as running and jumping.

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In recent years, much research interest has developed in image enhancement and haze removal techniques. With increasing demand for real time enhancement and haze removal, the need for efficient architecture incorporating both haze removal and enhancement is necessary. In this paper, we propose an architecture supporting both real-time Retinex-based image enhancement and haze removal, using a single module. Efficiently leveraging the similarity between Retinex-based image enhancement and haze removal algorithms, we have successfully proposed an architecture supporting both using a single module. The implementation results reveal that just 1% logic circuits overhead is required to support Retinex-based image enhancement in single mode and haze removal based on Retinex model. This reduction in computation complexity by using a single module reduces the processing and memory implications especially in mobile consumer electronics, as opposed to implementing them individually using different modules. Furthermore, we utilize image enhancement for transmission map estimation instead of soft matting, thereby avoiding further computation complexity which would affect our goal of realizing high frame-rate real time processing. Our FPGA implementation, operating at an optimum frequency of 125 MHz with 5.67 M total block memory bit size, supports WUXGA (1,920×1,200) 60 fps as well as 1080p60 color input. Our proposed design is competitive with existing state-of-the-art designs. Our proposal is tailored to enhance consumer electronic such as on-board cameras, active surveillance intrusion detection systems, autonomous cars, mobile streaming systems and robotics with low processing and memory requirements.

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