• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of visual communication & image representation >Multiexposure image fusion using intensity enhancement and detail extraction
【24h】

Multiexposure image fusion using intensity enhancement and detail extraction

机译：使用强度增强和细节提取的多重曝光图像融合

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In this study, a multiexposure image fusion approach using intensity enhancement and detail extraction is proposed. The N input low dynamic range (LDR) RGB color images are transformed into HSI color space. Intensity enhancement is achieved by CLAHE and homomorphic filtering. Gamma correction is used to compensate the nonlinear response of display devices, whereas "cross-image" median filtering is used to generate the reference intensity image. L-0 smoothing filter and weighted least squares (WLS) optimization are used to perform local and global detail extractions on the N processed LDR images, respectively. The N weighting maps of the N processed LDR images are estimated by spatial and cross-image consistencies and then refined by cross bilateral filtering. Finally, the multiresolution spline based scheme is used to perform multiexposure image fusion. Based on the experimental results obtained in this study, the performance of the proposed approach is better than those of four comparison approaches. (C) 2015 Elsevier Inc. All rights reserved.
机译：在这项研究中，提出了一种使用强度增强和细节提取的多重曝光图像融合方法。将N个输入的低动态范围（LDR）RGB彩色图像转换为HSI彩色空间。通过CLAHE和同态滤波可实现强度增强。伽玛校正用于补偿显示设备的非线性响应，而“跨图像”中值滤波用于生成参考强度图像。 L-0平滑滤波器和加权最小二乘（WLS）优化分别用于对N个经过处理的LDR图像执行局部和全局细节提取。通过空间和跨图像一致性来估计N个已处理LDR图像的N个权重图，然后通过交叉双边滤波进行精炼。最后，基于多分辨率样条的方案用于执行多曝光图像融合。根据本研究获得的实验结果，该方法的性能优于四种比较方法。 （C）2015 Elsevier Inc.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号