Ghost and Noise Removal in Exposure Fusion for High Dynamic Range Imaging

Lee, Dong‐Kyu; Park, Rae-Hong; Chang, Seunghyuk

doi:10.5121/ijcga.2014.4401

Cited by 3 publications

(2 citation statements)

References 36 publications

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“…Min et al [ 67 ] filter the set of images with spatio-temporal motion compensated anisotropic filters prior to HDR reconstruction. Lee et al [ 68 ] use sub-band architecture for fusion, with a weighted combination using a motion indicator function to avoid ghosting effects. The low frequency bands are filtered with a multi-resolution bilateral filter while the high frequency bands are filtered by soft thresholding.…”

Section: Related Workmentioning

confidence: 99%

Efficient joint noise removal and multi exposure fusion

2022

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Multi-exposure fusion (MEF) is a technique that combines different snapshots of the same scene, captured with different exposure times, into a single image. This combination process (also known as fusion) is performed in such a way that the parts with better exposure of each input image have a stronger influence. Therefore, in the result image all areas are well exposed. In this paper, we propose a new method that performs MEF and noise removal. Rather than denoising each input image individually and then fusing the obtained results, the proposed strategy jointly performs fusion and denoising in the Discrete Cosinus Transform (DCT) domain, which leads to a very efficient algorithm. The method takes advantage of spatio-temporal patch selection and collaborative 3D thresholding. Several experiments show that the obtained results are significantly superior to the existing state of the art.

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Section: Related Workmentioning

confidence: 99%

Efficient joint noise removal and multi exposure fusion

2022

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“…Min et al [58] filter the set of images by spatio-temporal motion compensated anisotropic filters prior to HDR reconstruction. Lee et al [47] use sub-band architecture for fusion, with a weighted combination using a motion indicator function to avoid ghosting effects. The low frequency bands are filtered with a multiresolution bilateral filter while the high frequency bands are filtered by soft thresholding.…”

Section: Joint Hdr and Noise Removalmentioning

confidence: 99%

Joint Denoising and Demosaicking of Raw Video Sequences

Buades

Duran

2018

2018 25th IEEE International Conference on Image Processing (ICIP)

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We propose a patch-based method for the simultaneous denoising and fusion of a sequence of RAW multi-exposed images. A spatio-temporal criterion is used to select similar patches along the sequence, and a weighted principal component analysis permits to both denoise and fuse the multi exposed data. The overall strategy permits to denoise and fuse the set of images without the need of recovering each denoised image in the multi-exposure set, leading to a very efficient procedure. Several experiments show that the proposed method permits to obtain state-of-the-art fusion results with real RAW data.

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