A generic parallel computational framework of lifting wavelet transform for online engineering surface filtration Yuanping Xua Chaolong Zhanga, b, ⁎
[email protected] Zhijie Xub Jiliu Zhouc Kaiwei Wangd Jian Huanga aSchool of Software Engineering, Chengdu University of Information Technology, No.24 Block 1, Xuefu Road, Chengdu 610225, People's Republic of China bSchool of Computing & Engineering, University of Huddersfield, Queensgate HD1 3DH, Huddersfield, UK cSchool of Computer Science, Chengdu University of Information Technology, No.24 Block 1, Xuefu Road, Chengdu 610225, People's Republic of China dSchool of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, People's Republic of China ⁎Corresponding author at: School of Software Engineering, Chengdu University of Information Technology, No.24 Block 1, Xuefu Road, Chengdu 610225, People's Republic of China. Abstract Nowadays, complex geometrical surface texture measurement and evaluation require advanced filtration techniques. Discrete wavelet transform (DWT), especially the second-generation wavelet (Lifting Wavelet Transform – LWT), is the most adopted one due to its unified and abundant characteristics in measured data processing, geometrical feature extraction, manufacturing process planning, and production monitoring. However, when dealing with varied complex functional surfaces, the computational payload for performing DWT in real-time often becomes a core bottleneck in the context of massive measured data and limited computational capacities. It is a more prominent