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  • 标题:High Dynamic Range Image Deghosting Using Spectral Angle Mapper
  • 本地全文:下载
  • 作者:Muhammad Murtaza Khan
  • 期刊名称:Computers
  • 电子版ISSN:2073-431X
  • 出版年度:2019
  • 卷号:8
  • 期号:1
  • 页码:15-31
  • DOI:10.3390/computers8010015
  • 出版社:MDPI Publishing
  • 摘要:The generation of high dynamic range (HDR) images in the presence of moving objects results in the appearance of blurred objects. These blurred objects are called ghosts. Over the past decade, numerous deghosting techniques have been proposed for removing blurred objects from HDR images. These methods may try to identify moving objects and maximize dynamic range locally or may focus on removing moving objects and displaying static objects while enhancing the dynamic range. The resultant image may suffer from broken/incomplete objects or noise, depending upon the type of methodology selected. Generally, deghosting methods are computationally intensive; however, a simple deghosting method may provide sufficiently acceptable results while being computationally inexpensive. Inspired by this idea, a simple deghosting method based on the spectral angle mapper (SAM) measure is proposed. The advantage of using SAM is that it is intensity independent and focuses only on identifying the spectral—i.e., color—similarity between two images. The proposed method focuses on removing moving objects while enhancing the dynamic range of static objects. The subjective and objective results demonstrate the effectiveness of the proposed method.
  • 关键词:deghosting; high dynamic range; spectral angle mapper; denoising deghosting ; high dynamic range ; spectral angle mapper ; denoising
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