A New Photoreceptor Model of Human Visual System for HDR Natural Luminance Perception

被引:0
|
作者
Liang, Lei [1 ]
Pan, Jeng-Shyang [1 ,2 ]
Zhuang, Yongjun [3 ]
机构
[1] Harbin Inst Technol, Shenzhen Grad Sch, Dept Comp Sci & Technol, Harbin, Heilongjiang, Peoples R China
[2] Fujian Univ Techol, Fujian Prov Key Lab Big Data Min & Applicat, Fuzhou, Fujian, Peoples R China
[3] Qihan Technol Co LTD, Qihan Res, Shenzhen, Peoples R China
来源
JOURNAL OF INTERNET TECHNOLOGY | 2018年 / 19卷 / 07期
关键词
Adaptive photoreceptor model; High dynamic range image; Tone mapping; Photorealistic image; RETINA;
D O I
10.3966/160792642018121907017
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The human visual system is a very complex system and the photoreceptors on the retina are mainly responsible for sensing the luminance of natural scenes. In this paper, a new model which can simulate the adaptive luminance characteristics of the human eye's photoreceptor cells is proposed. According to this model, a new tone mapping algorithm which can display high dynamic range (HDR) images on low dynamic range (LDR) display devices is presented. This technology make the final mapped image simulate the viewer's photorealistic in real scene. First, a HDR image was divided into bright, middle and dark regions, and the three corresponding response curves for each region were acquired. Then, each curve applied different weighting factors, which was obtained by counting the number of pixels within each region. Finally, the final tone mapping curve was synthesized. The proposed algorithm which does not require manually setting parameters has strong stability and it is easy to use. In a variety of experimental conditions for natural scenes, the proposed algorithm has a strong realism. The proposed algorithm was also compared with existing major tone mapping algorithm based on traditional photoreceptor model.
引用
收藏
页码:2146 / 2153
页数:8
相关论文
共 9 条
  • [1] A 100,000-to-1 high dynamic range (HDR) luminance display for investigating visual perception under real-world luminance dynamics
    Hung, Chou P.
    Callahan-Flintoft, Chloe
    Walker, Anthony J.
    Fedele, Paul D.
    Fluitt, Kim F.
    Odoemene, Onyekachi
    Harrison, Andre, V
    Vaughan, Barry D.
    Jaswa, Matthew S.
    Wei, Min
    JOURNAL OF NEUROSCIENCE METHODS, 2020, 338
  • [2] Mathematical Model of the Human Visual System
    Gulina Y.S.
    Koliuchkin V.Y.
    Trofimov N.E.
    Optical Memory and Neural Networks, 2018, 27 (4) : 219 - 234
  • [3] Classification of natural images inspired by the human visual system
    Davoodi, Paria
    Ezoji, Mehdi
    Sadeghnejad, Naser
    NEUROCOMPUTING, 2023, 518 : 60 - 69
  • [4] The squirrel as a rodent model of the human visual system
    Van Hooser, Stephen D.
    Nelson, Sacha B.
    VISUAL NEUROSCIENCE, 2006, 23 (05) : 765 - 778
  • [5] The visual system of zebrafish and its use to model human ocular Diseases
    Gestri, Gaia
    Link, Brian A.
    Neuhauss, Stephan C. F.
    DEVELOPMENTAL NEUROBIOLOGY, 2012, 72 (03) : 302 - 327
  • [6] Extended surround based neuromorphically implementable model of human visual system
    Sarkar, S
    Ghosh, K
    Bhaumik, K
    2005 INTERNATIONAL CONFERENCE ON INTELLIGENT SENSING AND INFORMATION PROCESSING, PROCEEDINGS, 2005, : 458 - 462
  • [7] A Tone-Mapping Technique Based on Histogram Using a Sensitivity Model of the Human Visual System
    Khan, Ishtiaq Rasool
    Rahardja, Susanto
    Khan, Muhammad Murtaza
    Movania, Muhammad Mobeen
    Abed, Fidaa
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2018, 65 (04) : 3469 - 3479
  • [8] A model of the FAD redox cycle describes the dynamics of the effect of the geomagnetic field on the human visual system
    Thoss, Franz
    Bartsch, Bengt
    BIOLOGICAL CYBERNETICS, 2017, 111 (5-6) : 347 - 352
  • [9] Human Visual System Model-Based Optimized Tone Mapping of High Dynamic Range Images
    Nam Hoang Nguyen
    Vo, Tu Van
    Lee, Chul
    IEEE ACCESS, 2021, 9 : 127343 - 127355