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Article ; Online: Deep compression network for enhancing numerical reconstruction quality of full-complex holograms.

Seo, Juyeon / Lee, Jaewoo / Lee, Juhyun / Ko, Hyunsuk

2023 Volume 31, Issue 15, Page(s) 24573–24597

Abstract: The field of digital holography has been significant developed in recent decades, however, the commercialization of digital holograms is still hindered by the issue of large data sizes. Due to the complex signal characteristics of digital holograms, ... ...

Abstract	The field of digital holography has been significant developed in recent decades, however, the commercialization of digital holograms is still hindered by the issue of large data sizes. Due to the complex signal characteristics of digital holograms, which are of interferometric nature, traditional codecs are not able to provide satisfactory coding efficiency. Furthermore, in a typical coding scenario, the hologram is encoded and then decoded, leading to a numerical reconstruction via a light wave propagation model. While previous researches have mainly focused on the quality of the decoded hologram, it is the numerical reconstruction that is visible to the viewer, and thus, its quality must also be taken into consideration when designing a coding solution. In this study, the coding performances of existing compression standards, JPEG2000 and HEVC-Intra, are evaluated on a set of digital holograms, then the limitations of these standards are analyzed. Subsequently, we propose a deep learning-based compression network for full-complex holograms that demonstrates superior coding performance when compared to the latest standard codecs such as VVC and JPEG-XL, in addition to JPEG2000 and HEVC. The proposed network incorporates not only the quality of the decoded hologram, but also the quality of the numerical reconstruction as distortion costs for network training. The experimental results validate that the proposed network provides superior objective coding efficiency and better visual quality compared to the existing methods.
Language	English
Publishing date	2023-07-19
Publishing country	United States
Document type	Journal Article
ZDB-ID	1491859-6
ISSN	1094-4087 ; 1094-4087
ISSN (online)	1094-4087
ISSN	1094-4087
DOI	10.1364/OE.494835
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Psychometric Properties of the Nine-Item Korean Internet Gaming Disorder Scale: Short Form.

Kim, Bin-Na / Ko, Hyunsuk

Cyberpsychology, behavior and social networking

2020 Volume 23, Issue 12, Page(s) 854–859

Abstract: The main objective of this study was to examine the psychometric properties of the Korean version of the Internet Gaming Disorder Scale-Short Form (K-IGDS9-SF), a brief self-report instrument developed to assess Internet gaming disorder (IGD) in ... ...

Abstract	The main objective of this study was to examine the psychometric properties of the Korean version of the Internet Gaming Disorder Scale-Short Form (K-IGDS9-SF), a brief self-report instrument developed to assess Internet gaming disorder (IGD) in accordance with the
MeSH term(s)	Adult ; Factor Analysis, Statistical ; Female ; Humans ; Impulsive Behavior ; Internet Addiction Disorder/psychology ; Loneliness ; Male ; Psychometrics ; Reproducibility of Results ; Republic of Korea ; Self Concept ; Self Report ; Surveys and Questionnaires ; Video Games/psychology
Language	English
Publishing date	2020-09-23
Publishing country	United States
Document type	Journal Article
ZDB-ID	2545735-4
ISSN	2152-2723 ; 2152-2715
ISSN (online)	2152-2723
ISSN	2152-2715
DOI	10.1089/cyber.2020.0227
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Video Quality Model of Compression, Resolution and Frame Rate Adaptation Based on Space-Time Regularities.

Lee, Dae Yeol / Kim, Jongho / Ko, Hyunsuk / Bovik, Alan C

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

2022 Volume 31, Page(s) 3644–3656

Abstract: Being able to accurately predict the visual quality of videos subjected to various combinations of dimension reduction protocols is of high interest to the streaming video industry, given rapid increases in frame resolutions and frame rates. In this ... ...

Abstract	Being able to accurately predict the visual quality of videos subjected to various combinations of dimension reduction protocols is of high interest to the streaming video industry, given rapid increases in frame resolutions and frame rates. In this direction, we have developed a video quality predictor that is sensitive to spatial, temporal, or space-time subsampling combined with compression. Our predictor is based on new models of space-time natural video statistics (NVS). Specifically, we model the statistics of divisively normalized difference between neighboring frames that are relatively displaced. In an extensive empirical study, we found that those paths of space-time displaced frame differences that provide maximal regularity against our NVS model generally align best with motion trajectories. Motivated by this, we built a new video quality prediction engine that extracts NVS features that represent how space-time directional regularities are disturbed by space-time distortions. Based on parametric models of these regularities, we compute features that are used to train a regressor that can accurately predict perceptual quality. As a stringent test of the new model, we apply it to the difficult problem of predicting the quality of videos subjected not only to compression, but also to downsampling in space and/or time. We show that the new quality model achieves state-of-the-art (SOTA) prediction performance on the new ETRI-LIVE Space-Time Subsampled Video Quality (STSVQ) and also on the AVT-VQDB-UHD-1 database.
Language	English
Publishing date	2022-05-26
Publishing country	United States
Document type	Journal Article
ISSN	1941-0042
ISSN (online)	1941-0042
DOI	10.1109/TIP.2022.3173810
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: HEVC extension for phase hologram compression.

Oh, Kwan-Jung / Ban, Hyunmin / Choi, Seungmi / Ko, Hyunsuk / Kim, Hui Yong

Optics express

2023 Volume 31, Issue 6, Page(s) 9146–9164

Abstract: Compressing digital holograms have growing attention nowadays due to their huge amount of original data sizes. Although many progresses have been reported for full-complex holograms, the coding performance for phase-only holograms (POHs) has been quite ... ...

Abstract	Compressing digital holograms have growing attention nowadays due to their huge amount of original data sizes. Although many progresses have been reported for full-complex holograms, the coding performance for phase-only holograms (POHs) has been quite limited so far. In this paper, we present a very efficient compression method for POHs. It extends the conventional video coding standard HEVC (High Efficiency Video Coding) in such a way that the standard can be able to compress not only the natural images but also the phase images effectively. First, we suggest a proper way to calculate differences, distances and clipped values for phase signals by considering the inherent periodicity of phases. Then, some of the HEVC encoding and decoding processes are modified accordingly. The experimental results show that the proposed extension significantly outperforms the original HEVC for POH video sequences; specifically, average BD-rate reductions of 63.3% and 65.5% are achieved in phase domain and numerical reconstruction domain, respectively. It is worth mentioning that the modified encoding & decoding processes are very minimal and also applicable to the VVC (Versatile Video Coding), which is a successor of the HEVC.
Language	English
Publishing date	2023-05-08
Publishing country	United States
Document type	Journal Article
ZDB-ID	1491859-6
ISSN	1094-4087 ; 1094-4087
ISSN (online)	1094-4087
ISSN	1094-4087
DOI	10.1364/OE.479281
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Performance analysis of versatile video coding for encoding phase-only hologram videos.

Kim, Yongrok / Shin, Won / Lee, Jaewoo / Oh, Kwan-Jung / Ko, Hyunsuk

Optics express

2023 Volume 31, Issue 23, Page(s) 38854–38877

Abstract: In recent decades, holographic technology has made significant progress with the development of novel hologram generation methods and three-dimensional rendering devices. Nevertheless, the substantial size of holographic data presents a significant ... ...

Abstract	In recent decades, holographic technology has made significant progress with the development of novel hologram generation methods and three-dimensional rendering devices. Nevertheless, the substantial size of holographic data presents a significant challenge to its practical applications and thus necessitates the implementation of an efficient coding solution. In this study, we evaluate the efficiency of various coding tools within the state-of-the-art video coding standard, Versatile Video Coding, for encoding video of computer-generated phase-only hologram. Specifically, we examine the coding performance of transform/in-loop filter/screen-content coding tools. Through extensive encoding experiments and various statistical analyses, we investigated the limitations of existing standard codecs that do not account for the unique signal characteristics of phase-only holograms (POHs). The effects of coding artifacts on the visual quality of numerical reconstructions rendered from compressed POHs are also analyzed in detail. These comprehensive performance evaluations will provide valuable insights for developing efficient coding strategies for POH videos.
Language	English
Publishing date	2023-11-28
Publishing country	United States
Document type	Journal Article
ZDB-ID	1491859-6
ISSN	1094-4087 ; 1094-4087
ISSN (online)	1094-4087
ISSN	1094-4087
DOI	10.1364/OE.502254
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: On the space-time statistics of motion pictures.

Lee, Dae Yeol / Ko, Hyunsuk / Kim, Jongho / Bovik, Alan C

Journal of the Optical Society of America. A, Optics, image science, and vision

2021 Volume 38, Issue 7, Page(s) 908–923

Abstract: It is well known that natural images possess statistical regularities that can be captured by bandpass decomposition and divisive normalization processes that approximate early neural processing in the human visual system. We expand on these studies and ... ...

Abstract	It is well known that natural images possess statistical regularities that can be captured by bandpass decomposition and divisive normalization processes that approximate early neural processing in the human visual system. We expand on these studies and present new findings on the properties of space-time natural statistics that are inherent in motion pictures. Our model relies on the concept of temporal bandpass (e.g., lag) filtering in lateral geniculate nucleus (LGN) and area V1, which is similar to smoothed frame differencing of video frames. Specifically, we model the statistics of the differences between adjacent or neighboring video frames that have been slightly spatially displaced relative to one another. We find that when these space-time differences are further subjected to locally pooled divisive normalization, statistical regularities (or lack thereof) arise that depend on the local motion trajectory. We find that bandpass and divisively normalized frame differences that are displaced along the motion direction exhibit stronger statistical regularities than for other displacements. Conversely, the direction-dependent regularities of displaced frame differences can be used to estimate the image motion (optical flow) by finding the space-time displacement paths that best preserve statistical regularity.
MeSH term(s)	Humans ; Motion Perception ; Neurons ; Primary Visual Cortex ; Visual Perception
Language	English
Publishing date	2021-07-15
Publishing country	United States
Document type	Journal Article
ZDB-ID	283633-6
ISSN	1520-8532 ; 1084-7529 ; 0740-3232
ISSN (online)	1520-8532
ISSN	1084-7529 ; 0740-3232
DOI	10.1364/JOSAA.413772
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Quality Prediction on Deep Generative Images.

Ko, Hyunsuk / Lee, Dae Yeol / Cho, Seunghyun / Bovik, Alan C

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

2020

Abstract: In recent years, deep neural networks have been utilized in a wide variety of applications including image generation. In particular, generative adversarial networks (GANs) are able to produce highly realistic pictures as part of tasks such as image ... ...

Abstract	In recent years, deep neural networks have been utilized in a wide variety of applications including image generation. In particular, generative adversarial networks (GANs) are able to produce highly realistic pictures as part of tasks such as image compression. As with standard compression, it is desirable to be able to automatically assess the perceptual quality of generative images to monitor and control the encode process. However, existing image quality algorithms are ineffective on GAN generated content, especially on textured regions and at high compressions. Here we propose a new "naturalness"-based image quality predictor for generative images. Our new GAN picture quality predictor is built using a multi-stage parallel boosting system based on structural similarity features and measurements of statistical similarity. To enable model development and testing, we also constructed a subjective GAN image quality database containing (distorted) GAN images and collected human opinions of them. Our experimental results indicate that our proposed GAN IQA model delivers superior quality predictions on the generative image datasets, as well as on traditional image quality datasets.
Language	English
Publishing date	2020-04-16
Publishing country	United States
Document type	Journal Article
ISSN	1941-0042
ISSN (online)	1941-0042
DOI	10.1109/TIP.2020.2987180
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: Space-Time Video Regularity and Visual Fidelity

Lee, Dae Yeol / Ko, Hyunsuk / Kim, Jongho / Bovik, Alan C.

Compression, Resolution and Frame Rate Adaptation

2021

Abstract: In order to be able to deliver today's voluminous amount of video contents through limited bandwidth channels in a perceptually optimal way, it is important to consider perceptual trade-offs of compression and space-time downsampling protocols. In this ... ...

Abstract	In order to be able to deliver today's voluminous amount of video contents through limited bandwidth channels in a perceptually optimal way, it is important to consider perceptual trade-offs of compression and space-time downsampling protocols. In this direction, we have studied and developed new models of natural video statistics (NVS), which are useful because high-quality videos contain statistical regularities that are disturbed by distortions. Specifically, we model the statistics of divisively normalized difference between neighboring frames that are relatively displaced. In an extensive empirical study, we found that those paths of space-time displaced frame differences that provide maximal regularity against our NVS model generally align best with motion trajectories. Motivated by this, we build a new video quality prediction engine that extracts NVS features from displaced frame differences, and combines them in a learned regressor that can accurately predict perceptual quality. As a stringent test of the new model, we apply it to the difficult problem of predicting the quality of videos subjected not only to compression, but also to downsampling in space and/or time. We show that the new quality model achieves state-of-the-art (SOTA) prediction performance compared on the new ETRI-LIVE Space-Time Subsampled Video Quality (STSVQ) database, which is dedicated to this problem. Downsampling protocols are of high interest to the streaming video industry, given rapid increases in frame resolutions and frame rates.
Keywords	Electrical Engineering and Systems Science - Image and Video Processing
Subject code	004
Publishing date	2021-03-30
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: On the Space-Time Statistics of Motion Pictures

Lee, Dae Yeol / Ko, Hyunsuk / Kim, Jongho / Bovik, Alan C.

2021

Abstract: It is well-known that natural images possess statistical regularities that can be captured by bandpass decomposition and divisive normalization processes that approximate early neural processing in the human visual system. We expand on these studies and ... ...

Abstract	It is well-known that natural images possess statistical regularities that can be captured by bandpass decomposition and divisive normalization processes that approximate early neural processing in the human visual system. We expand on these studies and present new findings on the properties of space-time natural statistics that are inherent in motion pictures. Our model relies on the concept of temporal bandpass (e.g. lag) filtering in LGN and area V1, which is similar to smoothed frame differencing of video frames. Specifically, we model the statistics of the differences between adjacent or neighboring video frames that have been slightly spatially displaced relative to one another. We find that when these space-time differences are further subjected to locally pooled divisive normalization, statistical regularities (or lack thereof) arise that depend on the local motion trajectory. We find that bandpass and divisively normalized frame-differences that are displaced along the motion direction exhibit stronger statistical regularities than for other displacements. Conversely, the direction-dependent regularities of displaced frame differences can be used to estimate the image motion (optical flow) by finding the space-time displacement paths that best preserve statistical regularity.
Keywords	Electrical Engineering and Systems Science - Image and Video Processing
Subject code	410
Publishing date	2021-01-29
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Subjective and Objective Study of Space-Time Subsampled Video Quality.

Lee, Dae Yeol / Paul, Somdyuti / Bampis, Christos G / Ko, Hyunsuk / Kim, Jongho / Jeong, Se Yoon / Homan, Blake / Bovik, Alan C

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

2022 Volume 31, Page(s) 934–948

Abstract: Video dimensions are continuously increasing to provide more realistic and immersive experiences to global streaming and social media viewers. However, increments in video parameters such as spatial resolution and frame rate are inevitably associated ... ...

Abstract	Video dimensions are continuously increasing to provide more realistic and immersive experiences to global streaming and social media viewers. However, increments in video parameters such as spatial resolution and frame rate are inevitably associated with larger data volumes. Transmitting increasingly voluminous videos through limited bandwidth networks in a perceptually optimal way is a current challenge affecting billions of viewers. One recent practice adopted by video service providers is space-time resolution adaptation in conjunction with video compression. Consequently, it is important to understand how different levels of space-time subsampling and compression affect the perceptual quality of videos. Towards making progress in this direction, we constructed a large new resource, called the ETRI-LIVE Space-Time Subsampled Video Quality (ETRI-LIVE STSVQ) database, containing 437 videos generated by applying various levels of combined space-time subsampling and video compression on 15 diverse video contents. We also conducted a large-scale human study on the new dataset, collecting about 15,000 subjective judgments of video quality. We provide a rate-distortion analysis of the collected subjective scores, enabling us to investigate the perceptual impact of space-time subsampling at different bit rates. We also evaluated and compare the performance of leading video quality models on the new database. The new ETRI-LIVE STSVQ database is being made freely available at (https://live.ece.utexas.edu/research/ETRI-LIVE_STSVQ/index.html).
Language	English
Publishing date	2022-01-06
Publishing country	United States
Document type	Journal Article
ISSN	1941-0042
ISSN (online)	1941-0042
DOI	10.1109/TIP.2021.3137658
Database	MEDical Literature Analysis and Retrieval System OnLINE

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