Fibonacci Exposure Bracketing for High Dynamic Range Imaging

Gupta, Mohit; Iso, Daisuke; Nayar, Shree K.

doi:10.1109/iccv.2013.186

Cited by 32 publications

(17 citation statements)

References 19 publications

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“…Both are iterative and limited to only two shots for building the HDR image. Finally, Gupta et al [26] proposed a Fibonacci-series-based bracketing set determination algorithm in which each exposure time is the sum of the previous two. This technique does not aim for full dynamic range recovery though, but image registration for HDR video.…”

Section: State Of the Artmentioning

confidence: 99%

Adaptive exposure estimation for high dynamic range imaging applied to natural scenes and daylight skies

2015

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Digital imaging of natural scenes and optical phenomena present on them (such as shadows, twilights, and crepuscular rays) can be a very challenging task because of the range spanned by the radiances impinging on the capture system. We propose a novel method for estimating the set of exposure times (bracketing set) needed to capture the full dynamic range of a scene with high dynamic range (HDR) content. The proposed method is adaptive to scene content and to any camera response and configuration, and it works on-line since the exposure times are estimated as the capturing process is ongoing. Besides, it requires no a priori information about scene content or radiance values. The resulting bracketing sets are minimal in the default method settings, but the user can set a tolerance for the maximum percentage of pixel population that is underexposed or saturated, which allows for a higher number of shots if a better signal-to-noise ratio (SNR) in the HDR scene is desired. This method is based on the use of the camera response function that is needed for building the HDR radiance map by stitching together several differently exposed low dynamic range images of the scene. The use of HDR imaging techniques converts our digital camera into a tool for measuring the relative radiance outgoing from each point of the scene, and for each color channel. This is important for accurate characterization of optical phenomena present in the atmosphere while not suffering any loss of information due to its HDR. We have compared our method with the most similar one developed so far [IEEE Trans. Image Process.17, 1864 (2008)]. Results of the experiments carried out for 30 natural scenes show that our proposed method equals or outperforms the previously developed best approach, with less shots and shorter exposure times, thereby asserting the advantage of being adaptive to scene content for exposure time estimation. As we can also tune the balance between capturing time and the SNR in our method, we have compared its SNR performance against that of Barakat's method as well as against a ground-truth HDR image of maximum SNR. Results confirm the success of the proposed method in exploiting its tunability to achieve the desired balance of total Δt and SNR.

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Section: State Of the Artmentioning

confidence: 99%

Adaptive exposure estimation for high dynamic range imaging applied to natural scenes and daylight skies

2015

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“…Subsequently, Hirakawa and Simon [17] showed that dynamic range could be extended within a single-shot based on color filtering of conventional cameras. Apart from these, many researches optimize exposure, noise and details recovery for HDR photography [13,16,14].…”

Section: Related Workmentioning

confidence: 99%

Unbounded High Dynamic Range Photography Using a Modulo Camera

Zhao

Shi

Fernandez-Cull

et al. 2015

2015 IEEE International Conference on Computational Photography (ICCP)

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“…Hereby, they assume that the image gradients stay almost constant under varying exposure times. In this context Gupta et al [12] propose an exposure bracketing technique to enhance the accuracy of existing optic flow methods that are applied for the pre-alignment step. Most related to our idea is the paper of Sen et al [13].…”

Section: Related Workmentioning

confidence: 99%

Simultaneous HDR and Optic Flow Computation

Hafner

Demetz

Weickert

2014

2014 22nd International Conference on Pattern Recognition

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Abstract-Camera shakes and moving objects pose a severe problem in the high dynamic range (HDR) reconstruction from differently exposed images. We present the first approach that simultaneously computes the aligned HDR composite as well as accurate displacement maps. In this way, we can not only cope with dynamic scenes but even precisely represent the underlying motion. We design our fully coupled model transparently in a well-founded variational framework. The proposed joint optimisation has beneficial effects, such as intrinsic ghost removal or HDR-coupled smoothing. Both the HDR images and the optic flows benefit substantially from these features and the induced mutual feedback. We demonstrate this with synthetic and realworld experiments.

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Fibonacci Exposure Bracketing for High Dynamic Range Imaging

Abstract: Exposure bracketing for high dynamic range (HDR)

Cited by 32 publications

References 19 publications

Adaptive exposure estimation for high dynamic range imaging applied to natural scenes and daylight skies

Adaptive exposure estimation for high dynamic range imaging applied to natural scenes and daylight skies

Unbounded High Dynamic Range Photography Using a Modulo Camera

Simultaneous HDR and Optic Flow Computation

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