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Dynamic Range Enhancing Methods for HDR Imaging and Displays

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dc.contributor.advisor조남익-
dc.contributor.author박재성-
dc.date.accessioned2018-05-28T16:18:54Z-
dc.date.available2018-05-28T16:18:54Z-
dc.date.issued2018-02-
dc.identifier.other000000149811-
dc.identifier.urihttps://hdl.handle.net/10371/140653-
dc.description학위논문 (박사)-- 서울대학교 대학원 : 공과대학 전기·정보공학부, 2018. 2. 조남익.-
dc.description.abstractHigh dynamic range (HDR) of the real-world scenes and human visual perception exceed the capabilities of current imaging and display systems. Most of the existing imaging and display systems cannot acquire or visualize the entire range of light information of the real world, and hence they have limits in providing realistic experience as human eyes can see. That is, they are low dynamic range (LDR) imaging systems. Traditional standards and ecosystem for image and video contents have been developed focusing on the LDR specification. For that reason, HDR imaging systems, image processing techniques and display devices have been in the spotlight to provide more realistic scenes as the human can see the real world. Recently, HDR technologies have gained momentum, and they have been affecting most of the research fields such as digital imaging, image processing, and display. They aim mainly to increase the dynamic range of visual contents when capturing, processing and visualizing the light information of the real world scene.

In this dissertation, dynamic range enhancing methods for imaging and display systems are presented. The first method is an image enhancement algorithm for undesirably illuminated images by using a single exposure, which is a single image high dynamic range (HDR) imaging method. The input image is first decomposed into illumination and reflectance components by employing an edge-preserving smoothing filter. Then the decomposed reflectance component is scaled up to improve the image details in bright areas. The estimated illumination component is locally and globally scaled up and down to generate several illumination images that correspond to certain camera exposure values which are different from the original. These illuminations are respectively combined with the enhanced reflectance to generate virtual multiple LDR images of multi-exposures. Finally, a detail-enhanced and illumination-equalized image is constructed by employing a tone fusion method that blends the multi-exposure images. A method to generate appropriate weighting maps for the proposed pseudo multi-exposure images is also presented. Also, the algorithm is extended to reverse tone mapping method that reconstructs HDR information from an LDR image for visualizing it on HDR displays. The feasibility is proven, and the performance is demonstrated by objective and subjective comparison with the conventional methods. This dynamic range enhancing method for LDR images is expected to be functional for all self-emission type HDR displays.

The second is to increase the dynamic range of liquid crystal display (LCD) which is one of the representative visualization devices. To expand the dynamic range of LCDs, conventional devices have employed localized backlight elements and their driving algorithms concerning local dimming methods. They are designed only to dim the backlight intensities of unit blocks based on the low-level features of the small image areas of input images. However, in this dissertation, human perception-based backlight intensity scaling algorithm is proposed. By keeping or boosting the backlight intensities of salient regions while suppressing in the others, the quality of salient regions and overall contrast are enhanced. Also, power can be saved by backlight intensity reduction in the non-salient areas, without loss of overall quality regarding human visual perception. In this backlight control process, the energy consumption in each backlight element is controlled by a parameter so that the sum of energies of overall backlight elements is kept within a limit. From the experiments, it is shown that the proposed algorithm stretches the dynamic range of backlight intensities (the range of display luminance) extensively. Thus the resulting images are shown to provide wide dynamic range and good image quality without any artifacts. This dynamic range enhancing algorithm can be an effective display system which is limited in energy consumption since it is very energy-efficient. Specifically, it is expected to be a reference of HDR-available luminance dual modulation systems such as high performing HDR LCDs.

Additionally, a wide range of experiments are conducted, and the results are presented to show the scalability and applicability of the HDR algorithm. As a result, it is proved that the proposed single image HDR algorithm can be extended to various HDR imaging methods, and also it can be applied as a pre- and post-processing units for various image processing systems.
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dc.description.tableofcontents1. Introduction 1
1.1 The Real World and Its Visualization 1
1.2 Motivation and Purpose of the Study 7
1.3 Contribution of the Study 9
1.4 Outline 12
2. High Dynamic Range Imaging and Displays 13
2.1 High Dynamic Range Imaging 13
2.1.1 Light information for vision 13
2.1.2 Dynamic range 15
2.1.3 Encoding HDR images 16
2.1.4 Generation of HDR content 19
2.2 High Dynamic Range Displays 35
2.2.1 Head mounted type HDR display 36
2.2.2 Projection type HDR display 37
2.2.3 Flat panel type HDR display 38
3. Related Work 43
3.1 Dynamic Range Enhancing Methods for LDR Images 43
3.1.1 Histogram equalization and its variations 43
3.1.2 Illumination adjustment methods 44
3.1.3 HDR Reverse tone mapping methods 53
3.2 Dynamic Range Enhancing Methods for LDR Displays: LCD 56
3.2.1 Basic of backlight dimming method 56
3.2.2 HVS-based backlight dimming methods 57
3.2.3 Limitation of the conventional strategies 57
4 Generation of High Dynamic Range Illumination from a Single Image for the Enhancement of Undesirably Illuminated Images 61
4.1 Motivation and Overview 62
4.2 Proposed Enhancement Algorithm 66
4.2.1 Image decomposition 66
4.2.2 Selective reflectance scaling 69
4.2.3 Virtual illumination generation 72
4.2.4 Tone reproduction 76
4.2.5 Weighting rules for luminance synthesis 78
4.3 Experiments and Discussions 80
4.3.1 Comparison with other methods 80
4.3.2 Discussions 87
4.4 Conclusion 91
5. Human Visual Perception-based Localized Backlight Scaling Method for High Dynamic Range LCDs 93
5.1 Motivation and Overview 93
5.2 Proposed Backlight Modulation Algorithm 97
5.2.1 Basics of local backlight adjustment algorithm 97
5.2.2 Saliency detection algorithm 99
5.2.3 Decision of dimming intensities and boosting weights 103
5.2.4 Backlight adjustment and power management method 106
5.2.5 Estimation and compensation of luminance loss 110
5.3 Experimental Results 111
5.3.1 Saliency detection results 113
5.3.2 Backlight intensity adjustment and power control 113
5.3.3 Estimation and compensation of luminance loss 118
5.3.4 Luminance and CR enhancement 120
5.3.5 Power consumption and similarity evaluation 122
5.3.6 Test for robustness 123
5.4 Discussion and Conclusion 125
6. Extension and Applications 127
6.1 Extension 127
6.1.1 Extension to a HDR Reverse Tone Mapper 127
6.1.2 Extension to a HDR Image Styler 129
6.2 Applications to Pre- and Post-processing Unit 133
6.2.1 HDR as a pre-processing unit 133
6.2.2 HDR as a post-processing unit 135
6.3 Application to Joint HDR and Super-Resolution Imaging 136
6.3.1 Super resolution by very deep convolutional networks 138
6.3.2 HDR/SR imaging system configurations 140
6.3.3 Experimental setup and results 142
7. Conclusions 153
Bibliography 157
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dc.formatapplication/pdf-
dc.format.extent99759633 bytes-
dc.format.mediumapplication/pdf-
dc.language.isoen-
dc.publisher서울대학교 대학원-
dc.subjectImaging Systems-
dc.subjectLow Dynamic Range-
dc.subjectHigh Dynamic Range Imaging-
dc.subjectDynamic Range Enhancement-
dc.subjectSingle Image HDR-
dc.subjectMulti-exposure Fusion-
dc.subjectTone Mapping and Reverse Tone Mapping Operators-
dc.subjectHDR Displays.-
dc.subject.ddc621.3-
dc.titleDynamic Range Enhancing Methods for HDR Imaging and Displays-
dc.typeThesis-
dc.description.degreeDoctor-
dc.contributor.affiliation공과대학 전기·정보공학부-
dc.date.awarded2018-02-
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