Multipurpose Image Colorization: A Novel Pipeline Using Convolutional Neural Networks

被引：0
作者：
Gomez Moreno, Ivannia [1 ,2 ]
Orozco-Rosas, Ulises [1 ]
Picosa, Kenia [1 ]
Rosing, Tajana [2 ]
机构：
[1] CETYS Univ, Ave CETYS Univ 4, Tajana Rosing 22210, Baja California, Mexico
[2] Univ Calif San Diego, 9500 Gilman Dr, La Jolla, CA 92093 USA
来源：
OPTICS AND PHOTONICS FOR INFORMATION PROCESSING XVIII | 2024年 / 13136卷
关键词：
Convolutional neural networks; Image processing; Deep learning; Colorization algorithms;
D O I：
10.1117/12.3028369
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The colorization of monochromatic images has demonstrated utility in enhancing human comprehension of images and boosting the accuracy of succeeding image-processing tasks. Nonetheless, current fully automated colorization methodologies often exhibit optimal performance based on the input image's nature and the employed algorithms' architectural specifics. In response to this challenge, this paper introduces a novel methodology aimed at effectively predicting the most suitable colorization model for a given input image. This comprehensive approach is characterized by exceptional accuracy across diverse datasets.
引用
收藏
页数：10
相关论文
共 34 条
  • [1] Albawi S, 2017, I C ENG TECHNOL
  • [2] Grayscale images colorization with convolutional neural networks
    An, Jiancheng
    Kpeyiton, Koffi Gagnon
    Shi, Qingnan
    [J]. SOFT COMPUTING, 2020, 24 (07) : 4751 - 4758
  • [3] Anitha A, 2023, EAI SPRINGER INNOVAT, P253, DOI 10.1007/978-3-031-20541-5_12
  • [4] Bergel A., 2020, Agile Artificial Intelligence in Pharo, V1
  • [5] CIFAKE: Image Classification and Explainable Identification of AI-Generated Synthetic Images
    Bird, Jordan J.
    Lotfi, Ahmad
    [J]. IEEE ACCESS, 2024, 12 : 15642 - 15650
  • [6] Cai YX, 2022, Arxiv, DOI arXiv:2212.11696
  • [7] ColorMedGAN: A Semantic Colorization Framework for Medical Images
    Chen, Shaobo
    Xiao, Ning
    Shi, Xinlai
    Yang, Yuer
    Tan, Huaning
    Tian, Jiajuan
    Quan, Yujuan
    [J]. APPLIED SCIENCES-BASEL, 2023, 13 (05):
  • [8] Chen X, 2022, Arxiv, DOI [arXiv:2209.06794, DOI 10.48550/ARXIV.2209.06794]
  • [9] Deng J, 2009, PROC CVPR IEEE, P248, DOI 10.1109/CVPRW.2009.5206848
  • [10] Learning Diverse Image Colorization
    Deshpande, Aditya
    Lu, Jiajun
    Yeh, Mao-Chuang
    Chong, Min Jin
    Forsyth, David
    [J]. 30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017), 2017, : 2877 - 2885
1234