Gradient-Based Feature Extraction from Raw Bayer Pattern Images

doi:10.1109/TIP.2021.3067166

	Gradient-Based Feature Extraction from Raw Bayer Pattern Images
	Wei Zhou; Ling Zhang; Shengyu Gao; Xin Lou
	2021
发表期刊	IEEE TRANSACTIONS ON IMAGE PROCESSING (IF:10.8[JCR-2023],12.1[5-Year])
ISSN	1057-7149
EISSN	1941-0042
卷号	30 页码:5122-5137
发表状态	已发表
DOI	10.1109/TIP.2021.3067166
摘要	In this paper, the impact of demosaicing on gradient extraction is studied and a gradient-based feature extraction pipeline based on raw Bayer pattern images is proposed. It is shown both theoretically and experimentally that the Bayer pattern images are applicable to the central difference gradient-based feature extraction algorithms with negligible performance degradation, as long as the arrangement of color filter array (CFA) patterns matches the gradient operators. The color difference constancy assumption, which is widely used in various demosaicing algorithms, is applied in the proposed Bayer pattern image-based gradient extraction pipeline. Experimental results show that the gradients extracted from Bayer pattern images are robust enough to be used in histogram of oriented gradients (HOG)-based pedestrian detection algorithms and shift-invariant feature transform (SIFT)-based matching algorithms. By skipping most of the steps in the image signal processing (ISP) pipeline, the computational complexity and power consumption of a computer vision system can be reduced significantly. © 1992-2012 IEEE.
关键词	Colorimetry Extraction Feature extraction Green computing Pipelines Bayer pattern images Computer vision system Demosaicing algorithm Gradient based feature Histogram of oriented gradients (HOG) Image signal processing Pedestrian detection Performance degradation Image color analysis Colored noise Histograms Signal processing algorithms Computer vision Gradient Bayer pattern image feature extraction demosaicing
URL	查看原文
收录类别	EI ; SCIE
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000655246800001
出版者	Institute of Electrical and Electronics Engineers Inc.
EI入藏号	20212310447993
EI主题词	Color image processing
EI分类号	619.1 Pipe, Piping and Pipelines ; 741.1 Light/Optics ; 802.3 Chemical Operations ; 941.4 Optical Variables Measurements
原始文献类型	Journal article (JA)
来源库	IEEE
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/133364
专题	信息科学与技术学院信息科学与技术学院_PI研究组_娄鑫组信息科学与技术学院_硕士生信息科学与技术学院_博士生
作者单位	School of Information Science and Technology, ShanghaiTech University, Shanghai, China
第一作者单位	信息科学与技术学院
第一作者的第一单位	信息科学与技术学院
推荐引用方式 GB/T 7714	Wei Zhou,Ling Zhang,Shengyu Gao,et al. Gradient-Based Feature Extraction from Raw Bayer Pattern Images[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2021,30:5122-5137.
APA	Wei Zhou,Ling Zhang,Shengyu Gao,&Xin Lou.(2021).Gradient-Based Feature Extraction from Raw Bayer Pattern Images.IEEE TRANSACTIONS ON IMAGE PROCESSING,30,5122-5137.
MLA	Wei Zhou,et al."Gradient-Based Feature Extraction from Raw Bayer Pattern Images".IEEE TRANSACTIONS ON IMAGE PROCESSING 30(2021):5122-5137.