Analysis of Implementing Mobile Heterogeneous Computing for Image Sequence Processing

• Aram BAEK,
• Kangwoon LEE,
• Jae-Gon KIM,
• Haechul CHOI,

Vol. 11, No. 10, October 30, 2017
10.3837/tiis.2017.10.014, Download Paper (Free):

• image processing
• Mobile Platform
• heterogeneous computing
• embedded GPU
• GPGPU.

Abstract

On mobile devices, image sequences are widely used for multimedia applications such as computer vision, video enhancement, and augmented reality. However, the real-time processing of mobile devices is still a challenge because of constraints and demands for higher resolution images. Recently, heterogeneous computing methods that utilize both a central processing unit (CPU) and a graphics processing unit (GPU) have been researched to accelerate the image sequence processing. This paper deals with various optimizing techniques such as parallel processing by the CPU and GPU, distributed processing on the CPU, frame buffer object, and double buffering for parallel and/or distributed tasks. Using the optimizing techniques both individually and combined, several heterogeneous computing structures were implemented and their effectiveness were analyzed. The experimental results show that the heterogeneous computing facilitates executions up to 3.5 times faster than CPU-only processing.

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