Performance evaluation of image noise reduction computing on a mobile platform

Abstract

Noise reduction is one of the most fundamental digital image processing challenges. On mobile devices, proper solutions for this task can significantly increase the output image quality making the use of a camera even more attractive for customers. The main challenge is that the processing time and energy efficiency must be optimized, since the response time and the battery life are critical factors for all mobile applications. To identify the solutions that maximizes the real-time performance, we compare several different implementations in terms of computational performance and energy efficiency. Specifically, we compare the OpenCL based design with multithreaded and NEON accelerated implementations and analyze them on the mobile platform. Based on the results of this study, the OpenCL framework provides a viable energy efficient alternative for implementing computer vision algorithms.