Institution
Dolby Laboratories
Company•Amsterdam, Netherlands•
About: Dolby Laboratories is a company organization based out in Amsterdam, Netherlands. It is known for research contribution in the topics: Audio signal & Audio signal flow. The organization has 956 authors who have published 1726 publications receiving 29456 citations.
Papers published on a yearly basis
Papers
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TL;DR: This paper proposes a fast algorithm that completes optimal 2-piecewise 2nd order polynomial inverse tone mapping in near constant time without quality degradation and shows that the proposed method achieves the same PSNR performance while saving 60 times computation time compared to the traditional exhaustive search.
Abstract: In a backward compatible HDR image/video compression, it is a general approach to reconstruct HDR from compressed
LDR as a prediction to original HDR, which is referred to as inverse tone mapping. Experimental results show that 2-
piecewise 2 nd order polynomial has the best mapping accuracy than 1 piece high order or 2-piecewise linear, but it is also
the most time-consuming method because to find the optimal pivot point to split LDR range to 2 pieces requires
exhaustive search. In this paper, we propose a fast algorithm that completes optimal 2-piecewise 2 nd order polynomial
inverse tone mapping in near constant time without quality degradation. We observe that in least square solution, each
entry in the intermediate matrix can be written as the sum of some basic terms, which can be pre-calculated into look-up
tables. Since solving the matrix becomes looking up values in tables, computation time barely differs regardless of the
number of points searched. Hence, we can carry out the most thorough pivot point search to find the optimal pivot that
minimizes MSE in near constant time. Experiment shows that our proposed method achieves the same PSNR
performance while saving 60 times computation time compared to the traditional exhaustive search in 2-piecewise 2 nd
order polynomial inverse tone mapping with continuous constraint.
14 citations
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21 Nov 2008TL;DR: In this article, the motion estimate is smoothed over the temporal window to facilitate aligning at least part of the image feature within the set of frames, where the regions of the two frames contain at least a portion of an image feature.
Abstract: For a frame set of a moving image sequence, a motion estimate is accessed. The motion estimate describes a change to a region of a reference frame with respect to at least one other frame. The reference frame and the other frames are displaced from each other within the frame set from over a temporal window. The regions of the two frames contain at least a portion of an image feature. The motion estimate is smoothed over the temporal window. The smoothing may facilitate aligning, at least in part, the image feature within the set of frames.
14 citations
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19 Jun 1998TL;DR: A split-band coding system combines multiple channels of input signals into various forms of composite signals and generates spatial-characteristic signals representing soundfield spatial characteristics in a plurality of frequency subbands as discussed by the authors.
Abstract: A split-band coding system combines multiple channels of input signals into various forms of composite signals and generates spatial-characteristic signals representing soundfield spatial characteristics in a plurality of frequency subbands. The spatial-characteristics signals may be generated in either or both of two forms. In a first form, the signal represents measures of signal levels for subband signals from the input channels. In a second form, the signal represents one or more apparent directions for the soundfield. The type of the spatial-characteristics signal may be adapted dynamically in response to a variety of criteria including input signal characteristics. Temporal smoothing and spectral smoothing of the spatial-characteristics signals may be applied in an encoder. Temporal smoothing and spectral smoothing may be applied to gain factors derived from the spatial-characteristics signals in a decoder.
14 citations
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10 Dec 2012TL;DR: In this article, a subset of offset values are located in a set of media data using a first type of one or more types of features, which are extractable from (e.g., derivable from components of) the media data.
Abstract: Low complexity detection of a time-wise position of a representative segment in media data is described. A subset of offset values is located in a set of offset values in media data using a first type of one or more types of features, which are extractable from (e.g., derivable from components of) the media data. The subset of offset values comprise values that are selected from the set of offset values based on one or more selection criteria. A set of candidate seed time points is identified based on the subset of offset values using a second type of the one or more types of features.
14 citations
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23 Jun 2011TL;DR: In this article, the authors present methods of determining and modifying the perceived loudness of a frequency domain audio signal where the frequency resolution and corresponding temporal coverage of the frequency domain information is not constant.
Abstract: Methods of, apparatuses for, and computer readable media having instructions thereon that when executed cause carrying out methods of determining and modifying the perceived loudness of a frequency domain audio signal where the frequency resolution, and corresponding temporal coverage of the frequency domain information is not constant. The frequency (and thus temporal) resolution of the perceived loudness processing is maintained constant at the longest block size. One method includes a block combiner and a loudness modification interpolator.
14 citations
Authors
Showing all 959 results
Name | H-index | Papers | Citations |
---|---|---|---|
Wolfgang Heidrich | 64 | 312 | 15854 |
Rabab K. Ward | 56 | 549 | 14364 |
Lorne A. Whitehead | 42 | 232 | 6661 |
Scott J. Daly | 41 | 230 | 5543 |
Michael E. Miller | 40 | 225 | 5264 |
Alireza Marandi | 39 | 140 | 6116 |
Wolfgang Stuerzlinger | 35 | 230 | 5192 |
Lars Villemoes | 33 | 180 | 2815 |
Joan Serrà | 31 | 139 | 4046 |
Dong Tian | 31 | 116 | 3621 |
Peng Yin | 30 | 133 | 2454 |
Ning Xu | 28 | 117 | 2705 |
Nicolas R. Tsingos | 28 | 110 | 2749 |
Panos Nasiopoulos | 27 | 271 | 3706 |
Zhibo Chen | 27 | 344 | 3385 |