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  • 1.
    Eilertsen, Gabriel
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    The high dynamic range imaging pipeline: Tone-mapping, distribution, and single-exposure reconstruction2018Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    Techniques for high dynamic range (HDR) imaging make it possible to capture and store an increased range of luminances and colors as compared to what can be achieved with a conventional camera. This high amount of image information can be used in a wide range of applications, such as HDR displays, image-based lighting, tone-mapping, computer vision, and post-processing operations. HDR imaging has been an important concept in research and development for many years. Within the last couple of years it has also reached the consumer market, e.g. with TV displays that are capable of reproducing an increased dynamic range and peak luminance.

    This thesis presents a set of technical contributions within the field of HDR imaging. First, the area of HDR video tone-mapping is thoroughly reviewed, evaluated and developed upon. A subjective comparison experiment of existing methods is performed, followed by the development of novel techniques that overcome many of the problems evidenced by the evaluation. Second, a largescale objective comparison is presented, which evaluates existing techniques that are involved in HDR video distribution. From the results, a first open-source HDR video codec solution, Luma HDRv, is built using the best performing techniques. Third, a machine learning method is proposed for the purpose of reconstructing an HDR image from one single-exposure low dynamic range (LDR) image. The method is trained on a large set of HDR images, using recent advances in deep learning, and the results increase the quality and performance significantly as compared to existing algorithms.

    The areas for which contributions are presented can be closely inter-linked in the HDR imaging pipeline. Here, the thesis work helps in promoting efficient and high-quality HDR video distribution and display, as well as robust HDR image reconstruction from a single conventional LDR image.

    Delarbeten
    1. A comparative review of tone-mapping algorithms for high dynamic range video
    Öppna denna publikation i ny flik eller fönster >>A comparative review of tone-mapping algorithms for high dynamic range video
    2017 (Engelska)Ingår i: Computer graphics forum (Print), ISSN 0167-7055, E-ISSN 1467-8659, Vol. 36, nr 2, s. 565-592Artikel i tidskrift (Refereegranskat) Published
    Abstract [en]

    Tone-mapping constitutes a key component within the field of high dynamic range (HDR) imaging. Its importance is manifested in the vast amount of tone-mapping methods that can be found in the literature, which are the result of an active development in the area for more than two decades. Although these can accommodate most requirements for display of HDR images, new challenges arose with the advent of HDR video, calling for additional considerations in the design of tone-mapping operators (TMOs). Today, a range of TMOs exist that do support video material. We are now reaching a point where most camera captured HDR videos can be prepared in high quality without visible artifacts, for the constraints of a standard display device. In this report, we set out to summarize and categorize the research in tone-mapping as of today, distilling the most important trends and characteristics of the tone reproduction pipeline. While this gives a wide overview over the area, we then specifically focus on tone-mapping of HDR video and the problems this medium entails. First, we formulate the major challenges a video TMO needs to address. Then, we provide a description and categorization of each of the existing video TMOs. Finally, by constructing a set of quantitative measures, we evaluate the performance of a number of the operators, in order to give a hint on which can be expected to render the least amount of artifacts. This serves as a comprehensive reference, categorization and comparative assessment of the state-of-the-art in tone-mapping for HDR video.

    Ort, förlag, år, upplaga, sidor
    WILEY, 2017
    Nationell ämneskategori
    Datavetenskap (datalogi)
    Identifikatorer
    urn:nbn:se:liu:diva-139637 (URN)10.1111/cgf.13148 (DOI)000404474000048 ()
    Konferens
    38th Annual Conference of the European-Association-for-Computer-Graphics (EUROGRAPHICS)
    Anmärkning

    Funding Agencies|Swedish Foundation for Strategic Research (SSF) [IIS11-0081]; Linkoping University Center for Industrial Information Technology (CENIIT); Swedish Research Council through the Linnaeus Environment CADICS

    Tillgänglig från: 2017-08-16 Skapad: 2017-08-16 Senast uppdaterad: 2018-05-15
    2. Evaluation of Tone Mapping Operators for HDR-Video
    Öppna denna publikation i ny flik eller fönster >>Evaluation of Tone Mapping Operators for HDR-Video
    2013 (Engelska)Ingår i: Computer graphics forum (Print), ISSN 0167-7055, E-ISSN 1467-8659, Vol. 32, nr 7, s. 275-284Artikel i tidskrift (Refereegranskat) Published
    Abstract [en]

    Eleven tone-mapping operators intended for video processing are analyzed and evaluated with camera-captured and computer-generated high-dynamic-range content. After optimizing the parameters of the operators in a formal experiment, we inspect and rate the artifacts (flickering, ghosting, temporal color consistency) and color rendition problems (brightness, contrast and color saturation) they produce. This allows us to identify major problems and challenges that video tone-mapping needs to address. Then, we compare the tone-mapping results in a pair-wise comparison experiment to identify the operators that, on average, can be expected to perform better than the others and to assess the magnitude of differences between the best performing operators.

    Ort, förlag, år, upplaga, sidor
    Wiley, 2013
    Nationell ämneskategori
    Teknik och teknologier
    Identifikatorer
    urn:nbn:se:liu:diva-104135 (URN)10.1111/cgf.12235 (DOI)000327310800029 ()
    Projekt
    VPS
    Tillgänglig från: 2014-02-07 Skapad: 2014-02-07 Senast uppdaterad: 2018-05-15Bibliografiskt granskad
    3. Real-time noise-aware tone mapping
    Öppna denna publikation i ny flik eller fönster >>Real-time noise-aware tone mapping
    2015 (Engelska)Ingår i: ACM Transactions on Graphics, ISSN 0730-0301, E-ISSN 1557-7368, ISSN 0730-0301, Vol. 34, nr 6, s. 198:1-198:15, artikel-id 198Artikel i tidskrift (Refereegranskat) Published
    Abstract [en]

    Real-time high quality video tone mapping is needed for manyapplications, such as digital viewfinders in cameras, displayalgorithms which adapt to ambient light, in-camera processing,rendering engines for video games and video post-processing. We propose a viable solution for these applications by designing a videotone-mapping operator that controls the visibility of the noise,adapts to display and viewing environment, minimizes contrastdistortions, preserves or enhances image details, and can be run inreal-time on an incoming sequence without any preprocessing. To ourknowledge, no existing solution offers all these features. Our novelcontributions are: a fast procedure for computing local display-adaptivetone-curves which minimize contrast distortions, a fast method for detailenhancement free from ringing artifacts, and an integrated videotone-mapping solution combining all the above features.

    Ort, förlag, år, upplaga, sidor
    New York, NY, USA: Association for Computing Machinery (ACM), 2015
    Nyckelord
    Tone mapping, high dynamic range video, display algorithms
    Nationell ämneskategori
    Datavetenskap (datalogi) Mediateknik
    Identifikatorer
    urn:nbn:se:liu:diva-122681 (URN)10.1145/2816795.2818092 (DOI)000363671200035 ()
    Konferens
    SIGGRAPH Aisa 2015
    Projekt
    VPS
    Forskningsfinansiär
    Stiftelsen för strategisk forskning (SSF)
    Tillgänglig från: 2015-11-14 Skapad: 2015-11-14 Senast uppdaterad: 2018-05-15
    4. A HIGH DYNAMIC RANGE VIDEO CODEC OPTIMIZED BY LARGE-SCALE TESTING
    Öppna denna publikation i ny flik eller fönster >>A HIGH DYNAMIC RANGE VIDEO CODEC OPTIMIZED BY LARGE-SCALE TESTING
    2016 (Engelska)Ingår i: 2016 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), IEEE , 2016, s. 1379-1383Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    While a number of existing high-bit depth video compression methods can potentially encode high dynamic range (HDR) video, few of them provide this capability. In this paper, we investigate techniques for adapting HDR video for this purpose. In a large-scale test on 33 HDR video sequences, we compare 2 video codecs, 4 luminance encoding techniques (transfer functions) and 3 color encoding methods, measuring quality in terms of two objective metrics, PU-MSSIM and HDR-VDP-2. From the results we design an open source HDR video encoder, optimized for the best compression performance given the techniques examined.

    Ort, förlag, år, upplaga, sidor
    IEEE, 2016
    Serie
    IEEE International Conference on Image Processing ICIP, ISSN 1522-4880
    Nyckelord
    High dynamic range (HDR) video; HDR video coding; perceptual image metrics
    Nationell ämneskategori
    Signalbehandling
    Identifikatorer
    urn:nbn:se:liu:diva-134106 (URN)10.1109/ICIP.2016.7532584 (DOI)000390782001093 ()978-1-4673-9961-6 (ISBN)
    Konferens
    23rd IEEE International Conference on Image Processing (ICIP)
    Tillgänglig från: 2017-01-22 Skapad: 2017-01-22 Senast uppdaterad: 2018-05-15
    5. HDR image reconstruction from a single exposure using deep CNNs
    Öppna denna publikation i ny flik eller fönster >>HDR image reconstruction from a single exposure using deep CNNs
    Visa övriga...
    2017 (Engelska)Ingår i: ACM Transactions on Graphics, ISSN 0730-0301, E-ISSN 1557-7368, Vol. 36, nr 6, artikel-id 178Artikel i tidskrift (Refereegranskat) Published
    Abstract [en]

    Camera sensors can only capture a limited range of luminance simultaneously, and in order to create high dynamic range (HDR) images a set of different exposures are typically combined. In this paper we address the problem of predicting information that have been lost in saturated image areas, in order to enable HDR reconstruction from a single exposure. We show that this problem is well-suited for deep learning algorithms, and propose a deep convolutional neural network (CNN) that is specifically designed taking into account the challenges in predicting HDR values. To train the CNN we gather a large dataset of HDR images, which we augment by simulating sensor saturation for a range of cameras. To further boost robustness, we pre-train the CNN on a simulated HDR dataset created from a subset of the MIT Places database. We demonstrate that our approach can reconstruct high-resolution visually convincing HDR results in a wide range of situations, and that it generalizes well to reconstruction of images captured with arbitrary and low-end cameras that use unknown camera response functions and post-processing. Furthermore, we compare to existing methods for HDR expansion, and show high quality results also for image based lighting. Finally, we evaluate the results in a subjective experiment performed on an HDR display. This shows that the reconstructed HDR images are visually convincing, with large improvements as compared to existing methods.

    Ort, förlag, år, upplaga, sidor
    ASSOC COMPUTING MACHINERY, 2017
    Nyckelord
    HDR reconstruction; inverse tone-mapping; deep learning; convolutional network
    Nationell ämneskategori
    Mediateknik
    Identifikatorer
    urn:nbn:se:liu:diva-143943 (URN)10.1145/3130800.3130816 (DOI)000417448700008 ()
    Konferens
    10th ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia
    Anmärkning

    Funding Agencies|Linkoping University Center for Industrial Information Technology (CENIIT); Swedish Science Council [2015-05180]; Wallenberg Autonomous Systems Program (WASP)

    Tillgänglig från: 2017-12-29 Skapad: 2017-12-29 Senast uppdaterad: 2018-05-15
  • 2.
    Eilertsen, Gabriel
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Forssén, Per-Erik
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Unger, Jonas
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    BriefMatch: Dense binary feature matching for real-time optical flow estimation2017Ingår i: Proceedings of the Scandinavian Conference on Image Analysis (SCIA17) / [ed] Puneet Sharma, Filippo Maria Bianchi, Springer, 2017, Vol. 10269, s. 221-233Konferensbidrag (Refereegranskat)
    Abstract [en]

    Research in optical flow estimation has to a large extent focused on achieving the best possible quality with no regards to running time. Nevertheless, in a number of important applications the speed is crucial. To address this problem we present BriefMatch, a real-time optical flow method that is suitable for live applications. The method combines binary features with the search strategy from PatchMatch in order to efficiently find a dense correspondence field between images. We show that the BRIEF descriptor provides better candidates (less outlier-prone) in shorter time, when compared to direct pixel comparisons and the Census transform. This allows us to achieve high quality results from a simple filtering of the initially matched candidates. Currently, BriefMatch has the fastest running time on the Middlebury benchmark, while placing highest of all the methods that run in shorter than 0.5 seconds.

  • 3.
    Eilertsen, Gabriel
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Kronander, Joel
    Linköpings universitet, Institutionen för teknik och naturvetenskap. Linköpings universitet, Tekniska fakulteten.
    Denes, Gyorgy
    University of Cambridge, England.
    Mantiuk, Rafal K.
    University of Cambridge, England.
    Unger, Jonas
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    HDR image reconstruction from a single exposure using deep CNNs2017Ingår i: ACM Transactions on Graphics, ISSN 0730-0301, E-ISSN 1557-7368, Vol. 36, nr 6, artikel-id 178Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Camera sensors can only capture a limited range of luminance simultaneously, and in order to create high dynamic range (HDR) images a set of different exposures are typically combined. In this paper we address the problem of predicting information that have been lost in saturated image areas, in order to enable HDR reconstruction from a single exposure. We show that this problem is well-suited for deep learning algorithms, and propose a deep convolutional neural network (CNN) that is specifically designed taking into account the challenges in predicting HDR values. To train the CNN we gather a large dataset of HDR images, which we augment by simulating sensor saturation for a range of cameras. To further boost robustness, we pre-train the CNN on a simulated HDR dataset created from a subset of the MIT Places database. We demonstrate that our approach can reconstruct high-resolution visually convincing HDR results in a wide range of situations, and that it generalizes well to reconstruction of images captured with arbitrary and low-end cameras that use unknown camera response functions and post-processing. Furthermore, we compare to existing methods for HDR expansion, and show high quality results also for image based lighting. Finally, we evaluate the results in a subjective experiment performed on an HDR display. This shows that the reconstructed HDR images are visually convincing, with large improvements as compared to existing methods.

  • 4.
    Eilertsen, Gabriel
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska högskolan.
    Larsson, Per
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska högskolan.
    Unger, Jonas
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska högskolan.
    A versatile material reflectance measurement system for use in production2011Ingår i: Proceedings of SIGRAD 2011. Evaluations of Graphics and Visualization — Efficiency, Usefulness, Accessibility, Usability, November 17–18, 2011, KTH, Stockholm, Sweden, Linköping University Electronic Press, 2011, s. 69-76Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper we present our developed bidirectional reflectance distribution capturing pipeline. It includes a constructed gonioreflectometer for reflectance measurements, as well as extensive software for operation, data visualization and parameter fitting of analytic models. Our focus is on the flexible user interface, aimed at material appearance creation for computer graphics, and targeted both for production and research employment.

    Key challenges have been in providing a user friendly and effective software for functioning in a production environment, abstracting the details of the calculations involved in the reflectance capturing and fitting. We show how a combination of well-tuned tools can make complex processes such as reflectance calibration, measurement and fitting highly automated in a fast and easy work-flow, from material scanning to model parameters optimized for use in rendering. At the same time, the developed software provides a modifiable interface for detailed control. The importance of having good reflectance visualizations is also demonstrated, where the software plotting tools are able to show vital details of a reflectance distribution, giving valuable insight in to a materials properties and a models accuracy of fit to measured data, on both a local and global level.

  • 5.
    Eilertsen, Gabriel
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Mantiuk, R. K.
    University of Cambridge, England.
    Unger, Jonas
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    A comparative review of tone-mapping algorithms for high dynamic range video2017Ingår i: Computer graphics forum (Print), ISSN 0167-7055, E-ISSN 1467-8659, Vol. 36, nr 2, s. 565-592Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Tone-mapping constitutes a key component within the field of high dynamic range (HDR) imaging. Its importance is manifested in the vast amount of tone-mapping methods that can be found in the literature, which are the result of an active development in the area for more than two decades. Although these can accommodate most requirements for display of HDR images, new challenges arose with the advent of HDR video, calling for additional considerations in the design of tone-mapping operators (TMOs). Today, a range of TMOs exist that do support video material. We are now reaching a point where most camera captured HDR videos can be prepared in high quality without visible artifacts, for the constraints of a standard display device. In this report, we set out to summarize and categorize the research in tone-mapping as of today, distilling the most important trends and characteristics of the tone reproduction pipeline. While this gives a wide overview over the area, we then specifically focus on tone-mapping of HDR video and the problems this medium entails. First, we formulate the major challenges a video TMO needs to address. Then, we provide a description and categorization of each of the existing video TMOs. Finally, by constructing a set of quantitative measures, we evaluate the performance of a number of the operators, in order to give a hint on which can be expected to render the least amount of artifacts. This serves as a comprehensive reference, categorization and comparative assessment of the state-of-the-art in tone-mapping for HDR video.

  • 6.
    Eilertsen, Gabriel
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Mantiuk, Rafal K.
    University of Cambridge, England.
    Unger, Jonas
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    A HIGH DYNAMIC RANGE VIDEO CODEC OPTIMIZED BY LARGE-SCALE TESTING2016Ingår i: 2016 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), IEEE , 2016, s. 1379-1383Konferensbidrag (Refereegranskat)
    Abstract [en]

    While a number of existing high-bit depth video compression methods can potentially encode high dynamic range (HDR) video, few of them provide this capability. In this paper, we investigate techniques for adapting HDR video for this purpose. In a large-scale test on 33 HDR video sequences, we compare 2 video codecs, 4 luminance encoding techniques (transfer functions) and 3 color encoding methods, measuring quality in terms of two objective metrics, PU-MSSIM and HDR-VDP-2. From the results we design an open source HDR video encoder, optimized for the best compression performance given the techniques examined.

  • 7.
    Eilertsen, Gabriel
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten. IRYSTEC, Canada.
    Mantiuk, Rafal K.
    University of Cambridge, England; IRYSTEC, Canada.
    Unger, Jonas
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten. IRYSTEC, Canada.
    REAL-TIME NOISE-AWARE TONE-MAPPING AND ITS USE IN LUMINANCE RETARGETING2016Ingår i: 2016 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), IEEE , 2016, s. 894-898Konferensbidrag (Refereegranskat)
    Abstract [en]

    With the aid of tone-mapping operators, high dynamic range images can be mapped for reproduction on standard displays. However, for large restrictions in terms of display dynamic range and peak luminance, limitations of the human visual system have significant impact on the visual appearance. In this paper, we use components from the real-time noise-aware tone-mapping to complement an existing method for perceptual matching of image appearance under different luminance levels. The refined luminance retargeting method improves subjective quality on a display with large limitations in dynamic range, as suggested by our subjective evaluation.

  • 8.
    Eilertsen, Gabriel
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Mantiuk, Rafal
    University of Cambridge.
    Unger, Jonas
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Real-time noise-aware tone mapping2015Ingår i: ACM Transactions on Graphics, ISSN 0730-0301, E-ISSN 1557-7368, ISSN 0730-0301, Vol. 34, nr 6, s. 198:1-198:15, artikel-id 198Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Real-time high quality video tone mapping is needed for manyapplications, such as digital viewfinders in cameras, displayalgorithms which adapt to ambient light, in-camera processing,rendering engines for video games and video post-processing. We propose a viable solution for these applications by designing a videotone-mapping operator that controls the visibility of the noise,adapts to display and viewing environment, minimizes contrastdistortions, preserves or enhances image details, and can be run inreal-time on an incoming sequence without any preprocessing. To ourknowledge, no existing solution offers all these features. Our novelcontributions are: a fast procedure for computing local display-adaptivetone-curves which minimize contrast distortions, a fast method for detailenhancement free from ringing artifacts, and an integrated videotone-mapping solution combining all the above features.

  • 9.
    Eilertsen, Gabriel
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik.
    Mantiuk, Rafal
    University of Cambridge, England.
    Unger, Jonas
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik.
    Single-frame Regularization for Temporally Stable CNNs2019Ingår i: IEEE Conference on Computer Vision and Pattern Recognition, 2019, s. 11176-11185Konferensbidrag (Refereegranskat)
    Abstract [en]

    Convolutional neural networks (CNNs) can model complicated non-linear relations between images. However, they are notoriously sensitive to small changes in the input. Most CNNs trained to describe image-to-image mappings generate temporally unstable results when applied to video sequences, leading to flickering artifacts and other inconsistencies over time. In order to use CNNs for video material, previous methods have relied on estimating dense frame-to-frame motion information (optical flow) in the training and/or the inference phase, or by exploring recurrent learning structures. We take a different approach to the problem, posing temporal stability as a regularization of the cost function. The regularization is formulated to account for different types of motion that can occur between frames, so that temporally stable CNNs can be trained without the need for video material or expensive motion estimation. The training can be performed as a fine-tuning operation, without architectural modifications of the CNN. Our evaluation shows that the training strategy leads to large improvements in temporal smoothness. Moreover, for small datasets the regularization can help in boosting the generalization performance to a much larger extent than what is possible with naive augmentation strategies.

  • 10.
    Eilertsen, Gabriel
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Unger, Jonas
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Mantiuk, Rafal
    University of Cambridge, UK.
    Evaluation of tone mapping operators for HDR video2016Ingår i: High dynamic range video: from acquisition to display and applications / [ed] Frédéric Dufaux, Patrick Le Callet, Rafal K. Mantiuk, Marta Mrak, London, United Kingdom: Academic Press, 2016, 1st, s. 185-206Kapitel i bok, del av antologi (Övrigt vetenskapligt)
    Abstract [en]

    Tone mapping of HDR-video is a challenging filtering problem. It is highly important to develop a framework for evaluation and comparison of tone mapping operators. This chapter gives an overview of different approaches for how evalation of tone mapping operators can be conducted, including experimental setups, choice of input data, choice of tone mapping operators, and the importance of parameter tweaking for fair comparisons. This chapter also gives examples of previous evaluations with a focus on the results from the most recent evaluation conducted by Eilertsen et. al [reference]. This results in a classification of the currently most commonly used tone mapping operators and overview of their performance and possible artifacts.

  • 11.
    Eilertsen, Gabriel
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska högskolan.
    Unger, Jonas
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska högskolan.
    Wanat, Robert
    Bangor University, United Kingdom.
    Mantiuk, Rafal
    Bangor University, United Kingdom.
    Perceptually based parameter adjustments for video processing operations2014Ingår i: ACM SIGGRAPH Talks 2014, ACM Press, 2014Konferensbidrag (Refereegranskat)
    Abstract [en]

    Extensive post processing plays a central role in modern video production pipelines. A problem in this context is that many filters and processing operators are very sensitive to parameter settings and that the filter responses in most cases are highly non-linear. Since there is no general solution for performing perceptual calibration of image and video operators automatically, it is often necessary to manually perform tweaking of multiple parameters. This is an iterative process which requires instant visual feedback of the result in both the spatial and temporal domains. Due to large filter kernels, computational complexity, high frame rate, and image resolution it is, however, often very time consuming to iteratively re-process and tweak long video sequences.We present a new method for rapidly finding the perceptual minima in high-dimensional parameter spaces of general video operators. The key idea of our algorithm is that the characteristics of an operator can be accurately described by interpolating between a small set of pre-computed parameter settings. By computing a perceptual linearization of the parameter space of a video operator, the user can explore this interpolated space to find the best set of parameters in a robust way. Since many operators are dependent on two or more parameters, we formulate this as a general optimization problem where we let the objective function be determined by the user’s image assessments. To demonstrate the usefulness of our approach we show a set of use cases (see the supplementary material) where our algorithm is applied to computationally expensive video operations.

  • 12.
    Eilertsen, Gabriel
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska högskolan.
    Unger, Jonas
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska högskolan.
    Wanat, Robert
    Bangor University, UK.
    Mantiuk, Rafal
    Bangor University, UK.
    Survey and Evaluation of Tone Mapping Operators for HDR-video2013Ingår i: Siggraph 2013 Talks, ACM Press, 2013Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    This work presents a survey and a user evaluation of tone mapping operators (TMOs) for high dynamic range (HDR) video, i.e. TMOs that explicitly include a temporal model for processing of variations in the input HDR images in the time domain. The main motivations behind this work is that: robust tone mapping is one of the key aspects of HDR imaging [Reinhard et al. 2006]; recent developments in sensor and computing technologies have now made it possible to capture HDR-video, e.g. [Unger and Gustavson 2007; Tocci et al. 2011]; and, as shown by our survey, tone mapping for HDR video poses a set of completely new challenges compared to tone mapping for still HDR images. Furthermore, video tone mapping, though less studied, is highly important for a multitude of applications including gaming, cameras in mobile devices, adaptive display devices and movie post-processing. Our survey is meant to summarize the state-of-the-art in video tonemapping and, as exemplified in Figure 1 (right), analyze differences in their response to temporal variations. In contrast to other studies, we evaluate TMOs performance according to their actual intent, such as producing the image that best resembles the real world scene, that subjectively looks best to the viewer, or fulfills a certain artistic requirement. The unique strength of this work is that we use real high quality HDR video sequences, see Figure 1 (left), as opposed to synthetic images or footage generated from still HDR images.

  • 13.
    Eilertsen, Gabriel
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska högskolan.
    Wanat, Robert
    Bangor University, Wales .
    Mantiuk, Rafal K.
    Bangor University, Wales .
    Unger, Jonas
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska högskolan.
    Evaluation of Tone Mapping Operators for HDR-Video2013Ingår i: Computer graphics forum (Print), ISSN 0167-7055, E-ISSN 1467-8659, Vol. 32, nr 7, s. 275-284Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Eleven tone-mapping operators intended for video processing are analyzed and evaluated with camera-captured and computer-generated high-dynamic-range content. After optimizing the parameters of the operators in a formal experiment, we inspect and rate the artifacts (flickering, ghosting, temporal color consistency) and color rendition problems (brightness, contrast and color saturation) they produce. This allows us to identify major problems and challenges that video tone-mapping needs to address. Then, we compare the tone-mapping results in a pair-wise comparison experiment to identify the operators that, on average, can be expected to perform better than the others and to assess the magnitude of differences between the best performing operators.

  • 14.
    Unger, Jonas
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Banterle, Francesco
    Visual Computing Laboratory at ISTI-CNR, Italy.
    Mantiuk, Rafal
    Computer Laboratory, University of Cambridge, UK.
    Eilertsen, Gabriel
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    The HDR-video pipeline: From capture and image reconstruction to compression and tone mapping2016Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    High dynamic range (HDR) video technology has gone through remarkable developments over the last few years;HDR-video cameras are being commercialized, new algorithms for color grading and tone mapping specifically designed for HDR-video have recently been proposed, and the first open source compression algorithms for HDR-video are becoming available. HDR-video represents a paradigm shift in imaging and computer graphics, which has and will continue to generate a range of both new research challenges and applications. This intermediate-level tutorial will give an in-depth overview of the full HDR-video pipeline present several examples of state-of-the-art algorithms and technology in HDR-video capture, tone mapping, compression and specific applications in computer graphics.

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