期刊文献+

明暗突变图像多区域光晕自适应消除仿真研究

Research on Multi-Area Halo Adaptive Elimination Simulation for Light/Dark Mutation Image
下载PDF
导出
摘要 解决明暗突变多区域光晕现象,对于提升降质图像质量具有重要意义。针对传统的光晕消除方法在处理高动态范围图像时,局部细节出现过增强,易在明暗对比强烈的部分产生大气光误判、光晕伪影以及运算耗时等问题,提出一种基于多尺度Retinex的明暗突变图像多区域光晕自适应消除方法。利用大气光校验方法对明暗突变图像候选大气光的有效性进行判断,去除高光区域的干扰,利用基于块偏移的透射率计算方法获得突变图像边缘保持的透射率,抑制光晕像素的数量。将明暗突变图像局部方差和复杂度构造引导滤波的自适应平滑增益,估计图像照度分量,在对数域对多尺度Retinex数学模型进行求解,获取消除图像多区域光晕和细节保持的多尺度反射分量。对反射分量根据灰度等级进行自适应增强,获得最终增强后的图像。实验结果表明,所提方法能够有效克服光照不均并自适应消除了光晕现象,运算速度远优于当前同类方法。 A method to adaptively eliminate multi -region light halo in light and shade mutation image based on multi - scale Retinex is presented. Firstly, the atmospheric light calibration method was used to judge the effective- ness of candidate atmospheric light in light and shade image, so as to remove the interference of highlight area. Then, the transmissivity calculation method based on block offset was used to obtain the transmissivity of the edge preservation of mutation image and suppress the number of light halo pixels. Moreover, the adaptive smoothing gain of guided filter was constructed based on the local variance and complexity of light and shade image and the illumina- tion component of image was estimated. Meanwhile, the multi - scale Retinex mathematical model was solved in the logarithmic domain to obtain multi - scale reflections component which eliminated the multi - region light halo and preserved detail of image. Finally, the reflection component was adaptively enhanced based on the gray level to obtain the final image. Simulation results show that the proposed method can effectively overcome the uneven illumination and adaptively eliminate the light halo phenomenon. Meanwhile, the computation speed is better than the current method.
作者 侯培文 HOU Pei - wen(Taiyuan University,Taiyuan Shanxi 030006,Chin)
机构地区 太原大学
出处 《计算机仿真》 北大核心 2018年第8期339-342,456,共5页 Computer Simulation
关键词 明暗 突变图像 多区域 光晕 自适应消除 Light and shade Mutation image Multi -region Light halo Adaptive elimination
  • 相关文献

参考文献10

二级参考文献105

  • 1刘楠,程咏梅,赵永强.基于加权暗通道的图像去雾方法[J].光子学报,2012,41(3):320-325. 被引量:23
  • 2周雅,晏磊,赵虎.增强现实系统光照模型建立研究[J].中国图象图形学报(A辑),2004,9(8):968-971. 被引量:17
  • 3徐正伟,吴成柯.二维形状的透视不变性识别[J].自动化学报,1995,21(4):431-439. 被引量:2
  • 4姚远,朱淼良,卢广.增强现实场景光源的实时检测方法和真实感渲染框架[J].计算机辅助设计与图形学学报,2006,18(8):1270-1275. 被引量:4
  • 5Kim S, Kang W, Lee E, et al. Wavelet-domain color image enhancement using filtered directional bases and frequency-adap- tive shrinkage [J]. IEEE Transactions on Consumer Electro- nics, 2010, 56 (2): 1063-1070.
  • 6Chen H, Tsai S S, Schroth G, et al. Robust text detection in natural, images with edge-enhanced maximally stable extremal regions [-C-] //18th IEEE International Conference on Image Processing. IEEE, 2011: 2609-2612.
  • 7Zhan B, Wu Y. Infrared image enhancement based on wavelet transformation and retinex [C] //2nd International Conference on Intelligent Human-Machine Systems and Cybernetics. IEEE, 2010: 313-316.
  • 8Fadili J, Starck J L. Curvelets and ridgelets [-M]. Computa- tional Complexity. Springer New York, 2012: 754-773.
  • 9Du X, Chen H, Liu Z, et al. Hyperspectral and high-resolu- tion image fusion based on second generation Bandelet transform [-J]. Optical Engineering, 2013, 52 (6): 067001.
  • 10Easley G R, Labate D, Patel V M. Directional multiseale pro- cessing of images using wavelets with composite dilations [J]. Journal of Mathematical Imaging and Vision, 2014, 48 (1): 13-34.

共引文献114

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部