Eliminating ghosting and exposure artifacts in image mosaics

Uyttendaele, Matt; Eden, A.; Skeliski, R.

doi:10.1109/cvpr.2001.991005

Cited by 273 publications

(202 citation statements)

References 10 publications

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“…This approach preserves contrast in the motion regions as regions from multiple images are combined. An additional approach to eliminating ghosting artifacts while creating a mosaic of different image exposures was proposed in [36]. In this work, we address this problem from a bottom-up segmentation perspective.…”

Section: Related Workmentioning

confidence: 99%

An Improved HDR Technique by Classification Method

Agarwal¹,

Shrivastava²,

Bisen³

2015

IJCA

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Now a day, HDR image is mostly used in applications of wide range such as next generation broadcast, digital cinema and digital photography, because of its high quality and its good expression ability. In our work we have improved an HDR (High Dimensional image) and changed it into multiple improved Low Dynamic Range (LDR) images. We further used multiple copies of the same image and classified differently as per new Low Dynamic Range. Hence we obtain many new exponentially improved images. These images can be further improved by further LDR technique. Finally, we combine all these images and obtain a final image. This final image will be better as compared to the original image. Hence we have an image which in itself will be improved version of the given image.

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Section: Related Workmentioning

confidence: 99%

An Improved HDR Technique by Classification Method

Agarwal¹,

Shrivastava²,

Bisen³

2015

IJCA

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“…Unfortunately, if the object is not fully contained in one of the overlapping images it might be bisected. Still based on the same idea of using image differences to localize moving objects in image panoramas, Uyttendaele et al [7] a method to suppress the ghosting effect in mosaic images due to moving objects, along with a procedure to adjust the exposure across multiple images, in order to eliminate visible shifts in brightness and hue. This approach was intended to deal with multiple overlaps, and the authors proposed the search for regions of difference (RODs) on the overlapping areas, only using information from one image per ROD.…”

Section: A Literature Reviewmentioning

confidence: 99%

“…On the one hand, transition smoothing methods [6], [7] fade the images along a common overlapping region in order to minimize the visibility of the seam. On the other hand, optimal seam finding algorithms [8], [9] focus on computing the joining boundary which reduces in a higher degree the photometric differences on its common area to achieve a non-noticeable transition.…”

Section: A Literature Reviewmentioning

confidence: 99%

Challenges of close-range underwater optical mapping

Prados¹,

García²,

Escartı́n³

et al. 2011

OCEANS 2011 IEEE - Spain

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Abstract-Underwater optical mapping often involves the use of image mosaicing techniques. High quality mosaicing requires the application of blending methods to achieve continuous and artifact-free mosaics. Image blending has a dilated history of over three decades in the terrestrial and aerial fields. Unfortunately, the nature of the underwater medium adds additional difficulties to the mosaicing and blending tasks. In this paper a survey of the blending methods is given, focusing the attention on its applicability to underwater mosaicing. Image acquisition is performed by Autonomous Underwater Vehicles (AUVs) or Remotely Operated Vehicles (ROVs) in the deep ocean, a medium with aggressive light absorption and disrupting scattering effects that requires of the use of artificial lighting. A comprehensive comparison of the basic features and limitations of some of the most important existing blending techniques is presented. The goal is the generation of seamless and visually pleasant large area photo-mosaics of the seafloor, free from double contouring, ghosting and other disturbing and common blending artifacts.

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“…(ii) Stitching of images snapped from different viewpoints, which can either be captured sequentially [20,[79][80][81][82][83] via a traditional digital camera or captured simultaneously via a camera array [84,85], i.e., in a panorama.…”

Section: Field Of Viewmentioning

confidence: 99%

An overview of computational photography

Suo

Dai

2012

Sci. China Inf. Sci.

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Computational photography is an emerging multidisciplinary field. Over the last two decades, it has integrated studies across computer vision, computer graphics, signal processing, applied optics and related disciplines. Researchers are exploring new ways to break through the limitations of traditional digital imaging for the benefit of photographers, vision and graphics researchers, and image processing programmers. Thanks to much effort in various associated fields, the large variety of issues related to these new methods of photography are described and discussed extensively in this paper. To give the reader the full picture of the voluminous literature related to computational photography, this paper briefly reviews the wide range of topics in this new field, covering a number of different aspects, including: (i) the various elements of computational imaging systems and new sampling and reconstruction mechanisms; (ii) the different image properties which benefit from computational photography, e.g. depth of field, dynamic range; and (iii) the sampling subspaces of visual scenes in the real world. Based on this systematic review of the previous and ongoing work in this field, we also discuss some open issues and potential new directions in computational photography. This paper aims to help the reader get to know this new field, including its history, ultimate goals, hot topics, research methodologies, and future directions, and thus build a foundation for further research and related developments.

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Eliminating ghosting and exposure artifacts in image mosaics

Cited by 273 publications

References 10 publications

An Improved HDR Technique by Classification Method

An Improved HDR Technique by Classification Method

Challenges of close-range underwater optical mapping

An overview of computational photography

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