Title :
Point cloud data enhancement based on homomorphic filter
Author :
Hongjuan Yang ; Jiwen Chen
Author_Institution :
Sch. of Inf. & Electr. Eng., Shandong Jianzhu Univ., Jinan, China
Abstract :
Point cloud data of complex product with small changes of surface has narrow data range, high spatial relativity and smooth data change. It is not sensitive to feature extraction and shape recognition. Homomorphic filter is introduced into point cloud data enhancement. Point cloud data reflecting the product shape and spacial relationship is divided into the low frequency part and the high frequency part. Spatial location change has little effect on the low frequency part. The high frequency part changes greatly with spatial location characteristics of the object itself. Homomorphic filter is designed to reduce the low frequency part and enhance high-frequency part. Point cloud data enhancement based on homomorphic filter is proposed. Example shows point cloud data enhancement based on homomorphic filter can convert non uniform distribution point cloud data to uniform distribution point cloud data, improving the contrast of point cloud data.
Keywords :
computer graphics; feature extraction; filtering theory; image enhancement; complex product; feature extraction; high-frequency part; homomorphic filter; low frequency part; nonuniform distribution point cloud data; point cloud data enhancement; product shape; shape recognition; smooth data change; spacial relationship; spatial location change; spatial location characteristic; Feature extraction; Frequency conversion; Frequency-domain analysis; Histograms; Lasers; Shape; Three-dimensional displays; data enhancement; homomorphic filter; point cloud data;
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-3278-8
DOI :
10.1109/ICSESS.2014.6933617
