Parallel curvature filter for high performance image processing

Wei Pan; Yuanhao Gong; Guoping Qiu

doi:10.1117/12.2520823

22 March 2019 Parallel curvature filter for high performance image processing

Wei Pan, Yuanhao Gong, Guoping Qiu

Proceedings Volume 11049, International Workshop on Advanced Image Technology (IWAIT) 2019; 110491I (2019) https://doi.org/10.1117/12.2520823
Event: 2019 Joint International Workshop on Advanced Image Technology (IWAIT) and International Forum on Medical Imaging in Asia (IFMIA), 2019, Singapore, Singapore

Abstract

Recently, curvature filter (CF) has been developed to implicitly minimize curvature for image processing problems such as smoothing and denoising. In this paper, we propose a parallel curvature filter (PCF) that performs on GPU which is much faster than the original CF on CPU. Inspired by Convolution Neural Networks processed by GPU, the convolution operations in curvature filter computation can be similarly paralleled by GPU so that the PCF on a single GPU can process 33.2 Giga pixels per second. Such performance allows it to work in the real-time applications such as video processing and biomedical image processing, where high performance is required. Our experiments confirm the efficiency and effectiveness of the PCF.

Citation Download Citation

Wei Pan, Yuanhao Gong, and Guoping Qiu "Parallel curvature filter for high performance image processing", Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 110491I (22 March 2019); https://doi.org/10.1117/12.2520823

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