efect detection of CMOS camera based on local entropy

doi:10.3778/j.issn.1002-8331.2009.20.022

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (20): 71-73.DOI: 10.3778/j.issn.1002-8331.2009.20.022

• 研发、设计、测试 • Previous Articles Next Articles

efect detection of CMOS camera based on local entropy

SHEN Ya-fen，LIU Chun-ping，WANG Zhao-hui

School of Computer Science and Technology，Soochow University，Suzhou，Jiangsu 215006，China

Received:2008-06-03 Revised:2008-08-21 Online:2009-07-11 Published:2009-07-11
Contact: SHEN Ya-fen

基于局部熵的CMOS摄像头疵点检测

沈雅芬，刘纯平，王朝晖

苏州大学计算机科学与技术学院，江苏苏州 215006

通讯作者: 沈雅芬

Abstract

Abstract: In the digital image performance testing system of CMOS camera，defect detection is crucial.This paper proposes a defect detection of CMOS camera based on local entropy.Compared to the former method of defect detection on the camera，the local entropy method is adaptive.Experimental results have shown that the proposed method is accurate and efficient for detecting defect on the camera.

Key words: local entropy, digital image, defect detection

摘要： 在CMOS摄像头数字图像性能检测系统中，疵点检测是关键内容。基于局部熵，提出了基于局部熵的CMOS摄像头疵点检测方法。与原有的摄像头疵点检测方法进行比较，局部熵方法是一种自适应的疵点检测方法。实验结果表明，该方法能够准确、有效地检测到摄像头的疵点。

关键词: 局部熵, 数字图像, 疵点检测

SHEN Ya-fen，LIU Chun-ping，WANG Zhao-hui. efect detection of CMOS camera based on local entropy[J]. Computer Engineering and Applications, 2009, 45(20): 71-73.

沈雅芬，刘纯平，王朝晖. 基于局部熵的CMOS摄像头疵点检测
[J]. 计算机工程与应用, 2009, 45(20): 71-73.

[1]	HU Hui, XU Zhengquan. Evaluation Method of Visual Security Based on Edge Similarity and Local Entropy Adaptive Fusion [J]. Computer Engineering and Applications, 2020, 56(12): 215-222.
[2]	HAN Ming1，2, WANG Jingtao1, MENG Junying1, LIU Jiaomin2. Energy Functional of Local Entropy Combined with Non-Convex Regularization for Image Segmentation [J]. Computer Engineering and Applications, 2019, 55(6): 160-167.
[3]	SHEN Xiajiong1，2, ZHANG Huidong1, HAN Daojun1，2. Method for SAR image road edge detection based on multi-window fusion [J]. Computer Engineering and Applications, 2018, 54(19): 164-171.
[4]	WANG Rong, WANG Jianxin, CHEN Xiang, SHENG Yu. Digital image experiment platform for heterogeneous resource integration [J]. Computer Engineering and Applications, 2018, 54(15): 185-191.
[5]	ZHANG Nan1, WANG Xuebin1, 2, DU Yazhi1. Sub-pixel digital image correlation method based on optimization of positions of points [J]. Computer Engineering and Applications, 2017, 53(3): 193-200.
[6]	WANG Shumei. Adaptive detection algorithm for small objects in image [J]. Computer Engineering and Applications, 2016, 52(1): 210-213.
[7]	HUANG Yu, HUANG Wenyan, ZHANG Wanrou, MA Wenhua. Michelson interference fringe counting method based on array CCD [J]. Computer Engineering and Applications, 2015, 51(9): 180-184.
[8]	LIN Chengda1, FANG Yihang1, CHANG Tingting1, JI Zheng2, ZHAI Ruifang3. Fine reconstruction of objects by integrating close range point clouds and digital images [J]. Computer Engineering and Applications, 2015, 51(21): 185-190.
[9]	FU You1, XU Wusheng2, XIE Kefu3. Adaptive image fusion rule based on quantum theory [J]. Computer Engineering and Applications, 2015, 51(21): 191-194.
[10]	XING Nan, ZHU Hong, WANG Dong, HOU Haolu. Authenticity of digital image detected algorithm based on multiple classifiers aggregation [J]. Computer Engineering and Applications, 2014, 50(24): 164-167.
[11]	YANG Hong, ZHOU Zhiping. Anti-forensic research of image sensor-pattern noise forger [J]. Computer Engineering and Applications, 2014, 50(18): 156-161.
[12]	HE Wentao, YE Xueyi, HE Zhiwei, WANG Yunlu. Similar neighborhood approach for image inpainting [J]. Computer Engineering and Applications, 2014, 50(13): 163-167.
[13]	WU Xingjia. Study on encryption technology based on Fresnel transform [J]. Computer Engineering and Applications, 2013, 49(12): 90-92.
[14]	DU Yazhi, WANG Xuebin. Digital image correlation method based on particle swarm optimization algorithm without subpixel interpolation [J]. Computer Engineering and Applications, 2012, 48(6): 200-204.
[15]	DU Yazhi, WANG Xuebin. Digital image correlation method based on Newton-Raphson method and particle swarm optimization algorithm [J]. Computer Engineering and Applications, 2012, 48(34): 184-189.

efect detection of CMOS camera based on local entropy

基于局部熵的CMOS摄像头疵点检测

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics