A Distorted Light Field Image Correction Method Based on Improved Hough Transform

被引:0
|
作者
Zhang, Ruihua [1 ]
Bi, Shubo [2 ]
机构
[1] Technician College, Nantong Vocational University, Nantong,226007, China
[2] School of Intelligent Manufacturing, Jiangsu College of Engineering and Technology, Nantong,226006, China
关键词
Feature extraction - Image enhancement - Signal to noise ratio;
D O I
10.2174/0126662558270259231122040821
中图分类号
学科分类号
摘要
Introduction: In using a camera to take photos, due to environmental limitations, uneven lighting can cause uneven distribution of the image light field, resulting in distortion of the image background and target, blurring of details, and distorted light field images. Method: In view of this, research is conducted on the correction of distorted light field images based on the Hough transform. First, the improved Hough transform is utilized to locate the four coordinates, the matrix information of the normal image is applied to calculate the corre-sponding parameter amount, and then the low-frequency part of the image spectrum is re-moved. Finally, it uses the Gaussian function for difference, inputs the original data, and gets the correction result of the distorted light field image. Result: The research results indicate that in the practical application of the distorted light field image correction algorithm based on the Hough transform, the improved Hough transform algorithm is superior to the traditional one. Conclusion: In comparative experiments, the research algorithm outperforms the other three algorithms, with an average color restoration of 93.76% and an average signal-to-noise ratio of 54.22dB. The superiority of the research algorithm has been verified, indicating that the research method can perfectly correct distorted light field images and achieve good correction results. © 2024 Bentham Science Publishers.
引用
收藏
页码:61 / 71
相关论文
共 50 条
  • [41] A fast and effective algorithm based on improved hough transform
    Ren Dongfeng
    Wang Qiubing
    Sun Fujun
    Journal of the Indian Society of Remote Sensing, 2016, 44 : 465 - 469
  • [42] Range image segmentation based on randomized Hough transform
    Ding, YH
    Ping, XJ
    Hu, M
    Wang, D
    PATTERN RECOGNITION LETTERS, 2005, 26 (13) : 2033 - 2041
  • [43] Image registration based on Hough transform and phase correlation
    Li, ZK
    Yang, XH
    Wu, LN
    PROCEEDINGS OF 2003 INTERNATIONAL CONFERENCE ON NEURAL NETWORKS & SIGNAL PROCESSING, PROCEEDINGS, VOLS 1 AND 2, 2003, : 956 - 959
  • [44] Lane detection and tracking based on improved Hough transform and least-squares method
    Sun, Peng
    Chen, Hui
    INTERNATIONAL SYMPOSIUM ON OPTOELECTRONIC TECHNOLOGY AND APPLICATION 2014: IMAGE PROCESSING AND PATTERN RECOGNITION, 2014, 9301
  • [45] Erythrometry method based on a modified Hough transform
    Zhdanov, I. N.
    Potapov, A. S.
    Shcherbakov, O. V.
    JOURNAL OF OPTICAL TECHNOLOGY, 2013, 80 (03) : 201 - 203
  • [46] An image localization system based on Gradient Hough Transform
    Liu, Yuqing
    Zhang, Jun
    Tian, Jinwen
    MIPPR 2015: REMOTE SENSING IMAGE PROCESSING, GEOGRAPHIC INFORMATION SYSTEMS, AND OTHER APPLICATIONS, 2015, 9815
  • [47] Measuring Method of Bearing Size Based on Improved Hough Transform of Circle Geometric Characteristics
    Gong, Lixiong
    INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS & STATISTICS, 2013, 40 (10): : 170 - 177
  • [48] An object detection method for quasi-circular fruits based on improved Hough transform
    Xie Z.
    Ji C.
    Guo X.
    Ren S.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2010, 26 (07): : 157 - 162
  • [49] Multi-targets attitude recognition method based on Hough and improved Radon transform
    Su, Xiuqin
    Lu, Tao
    Liang, Jinfeng
    2008 INTERNATIONAL CONFERENCE ON AUDIO, LANGUAGE AND IMAGE PROCESSING, VOLS 1 AND 2, PROCEEDINGS, 2008, : 344 - 350
  • [50] A Method to Detect Circle based on Hough Transform
    Wu, Mengjie
    Song, Zongxi
    Li, Baopeng
    Li, Feipeng
    Li, Bin
    Shen, Chao
    PROCEEDINGS OF THE FIRST INTERNATIONAL CONFERENCE ON INFORMATION SCIENCES, MACHINERY, MATERIALS AND ENERGY (ICISMME 2015), 2015, 126 : 2028 - 2031