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Olsson, Roger
Publications (10 of 71) Show all publications
Ahmad, W., Ghafoor, M., Tariq, S. A., Hassan, A., Sjöström, M. & Olsson, R. (2019). Computationally Efficient Light Field Image Compression Using a Multiview HEVC Framework. IEEE Access, 7, 143002-143014
Open this publication in new window or tab >>Computationally Efficient Light Field Image Compression Using a Multiview HEVC Framework
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2019 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 143002-143014Article in journal (Refereed) Published
Abstract [en]

The acquisition of the spatial and angular information of a scene using light eld (LF) technologies supplement a wide range of post-processing applications, such as scene reconstruction, refocusing, virtual view synthesis, and so forth. The additional angular information possessed by LF data increases the size of the overall data captured while offering the same spatial resolution. The main contributor to the size of captured data (i.e., angular information) contains a high correlation that is exploited by state-of-the-art video encoders by treating the LF as a pseudo video sequence (PVS). The interpretation of LF as a single PVS restricts the encoding scheme to only utilize a single-dimensional angular correlation present in the LF data. In this paper, we present an LF compression framework that efciently exploits the spatial and angular correlation using a multiview extension of high-efciency video coding (MV-HEVC). The input LF views are converted into multiple PVSs and are organized hierarchically. The rate-allocation scheme takes into account the assigned organization of frames and distributes quality/bits among them accordingly. Subsequently, the reference picture selection scheme prioritizes the reference frames based on the assigned quality. The proposed compression scheme is evaluated by following the common test conditions set by JPEG Pleno. The proposed scheme performs 0.75 dB better compared to state-of-the-art compression schemes and 2.5 dB better compared to the x265-based JPEG Pleno anchor scheme. Moreover, an optimized motionsearch scheme is proposed in the framework that reduces the computational complexity (in terms of the sum of absolute difference [SAD] computations) of motion estimation by up to 87% with a negligible loss in visual quality (approximately 0.05 dB).

Keywords
Compression, light field, MV-HEVC, plenoptic
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-37489 (URN)10.1109/ACCESS.2019.2944765 (DOI)
Available from: 2019-10-07 Created: 2019-10-07 Last updated: 2019-10-11Bibliographically approved
Li, Y., Olsson, R. & Sjöström, M. (2018). An analysis of demosaicing for plenoptic capture based on ray optics. In: Proceedings of 3DTV Conference 2018: . Paper presented at 3D at any scale and any perspective, 3-5 June 2018, Stockholm – Helsinki – Stockholm. , Article ID 8478476.
Open this publication in new window or tab >>An analysis of demosaicing for plenoptic capture based on ray optics
2018 (English)In: Proceedings of 3DTV Conference 2018, 2018, article id 8478476Conference paper, Published paper (Refereed)
Abstract [en]

The plenoptic camera is gaining more and more attention as it capturesthe 4D light field of a scene with a single shot and enablesa wide range of post-processing applications. However, the preprocessing steps for captured raw data, such as demosaicing, have been overlooked. Most existing decoding pipelines for plenoptic cameras still apply demosaicing schemes which are developed for conventional cameras. In this paper, we analyze the sampling pattern of microlens-based plenoptic cameras by ray-tracing techniques and ray phase space analysis. The goal of this work is to demonstrate guidelines and principles for demosaicing the plenoptic captures by taking the unique microlens array design into account. We show that the sampling of the plenoptic camera behaves differently from that of a conventional camera and the desired demosaicing scheme is depth-dependent.

Keywords
Light field, plenoptic camera, depth, image demosaicing
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-33618 (URN)10.1109/3DTV.2018.8478476 (DOI)000454903900008 ()2-s2.0-85056161198 (Scopus ID)978-1-5386-6125-3 (ISBN)
Conference
3D at any scale and any perspective, 3-5 June 2018, Stockholm – Helsinki – Stockholm
Available from: 2018-05-15 Created: 2018-05-15 Last updated: 2019-02-15Bibliographically approved
Ahmad, W., Sjöström, M. & Olsson, R. (2018). Compression scheme for sparsely sampled light field data based on pseudo multi-view sequences. In: OPTICS, PHOTONICS, AND DIGITAL TECHNOLOGIES FOR IMAGING APPLICATIONS V Proceedings of SPIE - The International Society for Optical Engineering: . Paper presented at SPIE Photonics Europe 2018 Strasbourg, France, 22-26 April 2018. SPIE - International Society for Optical Engineering, 10679, Article ID 106790M.
Open this publication in new window or tab >>Compression scheme for sparsely sampled light field data based on pseudo multi-view sequences
2018 (English)In: OPTICS, PHOTONICS, AND DIGITAL TECHNOLOGIES FOR IMAGING APPLICATIONS V Proceedings of SPIE - The International Society for Optical Engineering, SPIE - International Society for Optical Engineering, 2018, Vol. 10679, article id 106790MConference paper, Published paper (Refereed)
Abstract [en]

With the advent of light field acquisition technologies, the captured information of the scene is enriched by having both angular and spatial information. The captured information provides additional capabilities in the post processing stage, e.g. refocusing, 3D scene reconstruction, synthetic aperture etc. Light field capturing devices are classified in two categories. In the first category, a single plenoptic camera is used to capture a densely sampled light field, and in second category, multiple traditional cameras are used to capture a sparsely sampled light field. In both cases, the size of captured data increases with the additional angular information. The recent call for proposal related to compression of light field data by JPEG, also called “JPEG Pleno”, reflects the need of a new and efficient light field compression solution. In this paper, we propose a compression solution for sparsely sampled light field data. In a multi-camera system, each view depicts the scene from a single perspective. We propose to interpret each single view as a frame of pseudo video sequence. In this way, complete MxN views of multi-camera system are treated as M pseudo video sequences, where each pseudo video sequence contains N frames. The central pseudo video sequence is taken as base View and first frame in all the pseudo video sequences is taken as base Picture Order Count (POC). The frame contained in base view and base POC is labeled as base frame. The remaining frames are divided into three predictor levels. Frames placed in each successive level can take prediction from previously encoded frames. However, the frames assigned with last prediction level are not used for prediction of other frames. Moreover, the rate-allocation for each frame is performed by taking into account its predictor level, its frame distance and view wise decoding distance relative to the base frame. The multi-view extension of high efficiency video coding (MV-HEVC) is used to compress the pseudo multi-view sequences. The MV-HEVC compression standard enables the frames to take prediction in both direction (horizontal and vertical d), and MV-HEVC parameters are used to implement the proposed 2D prediction and rate allocation scheme. A subset of four light field images from Stanford dataset are compressed, using the proposed compression scheme on four bitrates in order to cover the low to high bit-rates scenarios. The comparison is made with state-of-art reference encoder HEVC and its real-time implementation X265. The 17x17 grid is converted into a single pseudo sequence of 289 frames by following the order explained in JPEG Pleno call for proposal and given as input to the both reference schemes. The rate distortion analysis shows that the proposed compression scheme outperforms both reference schemes in all tested bitrate scenarios for all test images. The average BD-PSNR gain is 1.36 dB over HEVC and 2.15 dB over X265.

Place, publisher, year, edition, pages
SPIE - International Society for Optical Engineering, 2018
Series
Proceedings of SPIE, ISSN 0277-786X, E-ISSN 1996-756X
Keywords
Light field, MV-HEVC, Compression, Plenoptic, Multi-Camera
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-33352 (URN)10.1117/12.2315597 (DOI)000452663000017 ()2-s2.0-85052527607 (Scopus ID)
Conference
SPIE Photonics Europe 2018 Strasbourg, France, 22-26 April 2018
Available from: 2018-03-26 Created: 2018-03-26 Last updated: 2019-01-08Bibliographically approved
Boström, L., Sjöström, M., Karlsson, H., Sundgren, M., Andersson, M., Olsson, R. & Åhlander, J. (2018). Digital visualisering i skolan: Mittuniversitetets slutrapport från förstudien. Sundsvall: Mittuniversitetet
Open this publication in new window or tab >>Digital visualisering i skolan: Mittuniversitetets slutrapport från förstudien
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2018 (Swedish)Report (Other academic)
Abstract [sv]

Den här studiens syfte har varit tvåfaldigt, nämligen att testa alternativa lärmetoder via ett digitalt läromedel i matematik i en kvasiexperimentell studie samt att tillämpa metoder av användarupplevelser för interaktiva visualiseringar, och därigenom öka kunskapen kring hur upplevd kvalitet beror på använd teknik. Pilotstudien sätter också fokus på flera angelägna områden inom skolutveckling både regionalt och nationellt samt viktiga aspekter när det gäller kopplingen teknik, pedagogik och utvärderingsmetoder inom “den tekniska delen”. Det förra handlar om sjunkande matematikresultat i skolan, praktiknära skolforskning, stärkt digital kompetens, visualisering och lärande samt forskning om visualisering och utvärdering. Den senare svarar på frågor om vilka tekniska lösningar som tidigare använts och med vilket syfte har de skapats samt hur visualiseringar har utvärderats enligt läroböcker och i forskningslitteratur.

 

När det gäller elevernas resultat, en av de stora forskningsfrågorna i studien, så fann vi inga signifikanta skillnader mellan traditionell undervisning och undervisning med visualiseringsläromedlet (3D). Beträffande elevers attityder till matematikmomentet kan konstateras att i kontrollgruppen för årskurs 6 förbättrades attityden signifikans, men inte i klass 8. Gällande flickors och pojkars resultat och attityder kan vi konstatera att flickorna i båda klasserna hade bättre förkunskaper än pojkarna samt att i årskurs 6 var flickorna mer positiva till matematikmomentet än pojkarna i kontrollgruppen. Därutöver kan vi inte skönja några signifikanta skillnader. Andra viktiga rön i studien var att provkonstruktionen inte var optimal samt att tiden för provgenomförande har stor betydelse när på dagen det genomfördes. Andra resultat resultaten i den kvalitativa analysen pekar på positiva attityder och beteenden från eleverna vid arbetet med det visuella läromedlet. Elevernas samarbete och kommunikation förbättrades under lektionerna. Vidare pekade lärarna på att med 3D-läromedlet gavs större möjligheter till att stimulera flera sinnen under lärprocessen. En tydlig slutsats är att 3D-läromedlet är ett viktigt komplement i undervisningen, men kan inte användas helt självt.

 

Vi kan varken sälla oss till de forskare som anser att 3D-visualisering är överlägset som läromedel för elevers resultat eller till de forskare som varnar för dess effekter för elevers kognitiva överbelastning.  Våra resultat ligger mer i linje med de slutsatser Skolforskningsinstitutet (2017) drar, nämligen att undervisning med digitala läromedel i matematik kan ha positiva effekter, men en lika effektiv undervisning kan möjligen designas på andra sätt. Däremot pekar resultaten i vår studie på ett flertal störningsmoment som kan ha påverkat möjliga resultat och behovet av god teknologin och välutvecklade programvaror.

 

I studien har vi analyserat resultaten med hjälp av två övergripande ramverk för integrering av teknikstöd i lärande, SAMR och TPACK. Det förra ramverket bidrog med en taxonomi vid diskussionen av hur väl teknikens möjligheter tagits tillvara av läromedel och i läraktiviteter, det senare för en diskussion om de didaktiska frågeställningarna med fokus på teknikens roll. Båda aspekterna är högaktuella med tanke på den ökande digitaliseringen i skolan.

 

Utifrån tidigare forskning och denna pilotstudie förstår vi att det är viktigt att designa forskningsmetoderna noggrant. En randomisering av grupper vore önskvärt. Prestandamått kan också vara svåra att välja. Tester där personer får utvärdera användbarhet (usability) och användarupplevelse (user experience, UX) baserade på både kvalitativa och kvantitativa metoder blir viktiga för själva användandet av tekniken, men det måste till ytterligare utvärderingar för att koppla tekniken och visualiseringen till kvaliteten i lärandet och undervisningen. Flera metoder behövs således och det blir viktigt med samarbete mellan olika ämnen och discipliner.

Place, publisher, year, edition, pages
Sundsvall: Mittuniversitetet, 2018. p. 60
National Category
Pedagogical Work
Identifiers
urn:nbn:se:miun:diva-35376 (URN)
Available from: 2018-12-31 Created: 2018-12-31 Last updated: 2019-01-07Bibliographically approved
Dima, E., Sjöström, M., Olsson, R., Kjellqvist, M., Litwic, L., Zhang, Z., . . . Flodén, L. (2018). LIFE: A Flexible Testbed For Light Field Evaluation. In: : . Paper presented at 2018 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON), Stockholm – Helsinki – Stockholm, 3-5 June 2018. , Article ID 8478550.
Open this publication in new window or tab >>LIFE: A Flexible Testbed For Light Field Evaluation
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2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Recording and imaging the 3D world has led to the use of light fields. Capturing, distributing and presenting light field data is challenging, and requires an evaluation platform. We define a framework for real-time processing, and present the design and implementation of a light field evaluation system. In order to serve as a testbed, the system is designed to be flexible, scalable, and able to model various end-to-end light field systems. This flexibility is achieved by encapsulating processes and devices in discrete framework systems. The modular capture system supports multiple camera types, general-purpose data processing, and streaming to network interfaces. The cloud system allows for parallel transcoding and distribution of streams. The presentation system encapsulates rendering and display specifics. The real-time ability was tested in a latency measurement; the capture and presentation systems process and stream frames within a 40 ms limit.

Keywords
Multiview, 3DTV, Light field, Distributed surveillance, 360 video
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:miun:diva-33620 (URN)000454903900016 ()2-s2.0-85056147245 (Scopus ID)978-1-5386-6125-3 (ISBN)
Conference
2018 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON), Stockholm – Helsinki – Stockholm, 3-5 June 2018
Projects
LIFE Project
Funder
Knowledge Foundation, 20140200
Available from: 2018-05-15 Created: 2018-05-15 Last updated: 2019-02-15Bibliographically approved
Conti, C., Soares, L. D., Nunes, P., Perra, C., Assunção, P. A., Sjöström, M., . . . Jennehag, U. (2018). Light Field Image Compression. In: Assunção, Pedro Amado, Gotchev, Atanas (Ed.), 3D Visual Content Creation, Coding and Delivery: (pp. 143-176). Cham: Springer
Open this publication in new window or tab >>Light Field Image Compression
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2018 (English)In: 3D Visual Content Creation, Coding and Delivery / [ed] Assunção, Pedro Amado, Gotchev, Atanas, Cham: Springer, 2018, p. 143-176Chapter in book (Refereed)
Place, publisher, year, edition, pages
Cham: Springer, 2018
Series
Signals and Communication Technology, ISSN 1860-4862
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-34382 (URN)2-s2.0-85063129881 (Scopus ID)978-3-319-77842-6 (ISBN)
Available from: 2018-09-13 Created: 2018-09-13 Last updated: 2019-05-22Bibliographically approved
Ahmad, W., Vagharshakyan, S., Sjöström, M., Gotchev, A., Bregovic, R. & Olsson, R. (2018). Shearlet Transform Based Prediction Scheme for Light Field Compression. In: : . Paper presented at Data Compression Conference (DCC 2018),Snowbird, Utah, US, March 27 - March 30, 2018.
Open this publication in new window or tab >>Shearlet Transform Based Prediction Scheme for Light Field Compression
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2018 (English)Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

Light field acquisition technologies capture angular and spatial information ofthe scene. The spatial and angular information enables various post processingapplications, e.g. 3D scene reconstruction, refocusing, synthetic aperture etc at theexpense of an increased data size. In this paper, we present a novel prediction tool forcompression of light field data acquired with multiple camera system. The captured lightfield (LF) can be described using two plane parametrization as, L(u, v, s, t), where (u, v)represents each view image plane coordinates and (s, t) represents the coordinates of thecapturing plane. In the proposed scheme, the captured LF is uniformly decimated by afactor d in both directions (in s and t coordinates), resulting in a sparse set of views alsoreferred to as key views. The key views are converted into a pseudo video sequence andcompressed using high efficiency video coding (HEVC). The shearlet transform basedreconstruction approach, presented in [1], is used at the decoder side to predict thedecimated views with the help of the key views.Four LF images (Truck, Bunny from Stanford dataset, Set2 and Set9 from High DensityCamera Array dataset) are used in the experiments. Input LF views are converted into apseudo video sequence and compressed with HEVC to serve as anchor. Rate distortionanalysis shows the average PSNR gain of 0.98 dB over the anchor scheme. Moreover, inlow bit-rates, the compression efficiency of the proposed scheme is higher compared tothe anchor and on the other hand the performance of the anchor is better in high bit-rates.Different compression response of the proposed and anchor scheme is a consequence oftheir utilization of input information. In the high bit-rate scenario, high quality residualinformation enables the anchor to achieve efficient compression. On the contrary, theshearlet transform relies on key views to predict the decimated views withoutincorporating residual information. Hence, it has inherit reconstruction error. In the lowbit-rate scenario, the bit budget of the proposed compression scheme allows the encoderto achieve high quality for the key views. The HEVC anchor scheme distributes the samebit budget among all the input LF views that results in degradation of the overall visualquality. The sensitivity of human vision system toward compression artifacts in low-bitratecases favours the proposed compression scheme over the anchor scheme.

National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-33356 (URN)
Conference
Data Compression Conference (DCC 2018),Snowbird, Utah, US, March 27 - March 30, 2018
Available from: 2018-03-27 Created: 2018-03-27 Last updated: 2018-06-11
Ahmad, W., Olsson, R. & Sjöström, M. (2018). Towards a generic compression solution for densely and sparsely sampled light field data. In: Proceedings of 25TH IEEE International Conference On Image Processing: . Paper presented at 25TH IEEE International Conference On Image Processing (ICIP), Athens, Greece, October 7-10, 2018 (pp. 654-658). , Article ID 8451051.
Open this publication in new window or tab >>Towards a generic compression solution for densely and sparsely sampled light field data
2018 (English)In: Proceedings of 25TH IEEE International Conference On Image Processing, 2018, p. 654-658, article id 8451051Conference paper, Published paper (Refereed)
Abstract [en]

Light field (LF) acquisition technologies capture the spatial and angular information present in scenes. The angular information paves the way for various post-processing applications such as scene reconstruction, refocusing, and synthetic aperture. The light field is usually captured by a single plenoptic camera or by multiple traditional cameras. The former captures a dense LF, while the latter captures a sparse LF. This paper presents a generic compression scheme that efficiently compresses both densely and sparsely sampled LFs. A plenoptic image is converted into sub-aperture images, and each sub-aperture image is interpreted as a frame of a multiview sequence. In comparison, each view of the multi-camera system is treated as a frame of a multi-view sequence. The multi-view extension of high efficiency video coding (MVHEVC) is used to encode the pseudo multi-view sequence.This paper proposes an adaptive prediction and rate allocation scheme that efficiently compresses LF data irrespective of the acquisition technology used.

Keywords
Light field, plenoptic, Multi-camera, MVHEVC
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-34283 (URN)10.1109/ICIP.2018.8451051 (DOI)000455181500132 ()2-s2.0-85062918597 (Scopus ID)978-1-4799-7061-2 (ISBN)
Conference
25TH IEEE International Conference On Image Processing (ICIP), Athens, Greece, October 7-10, 2018
Funder
EU, Horizon 2020
Available from: 2018-08-20 Created: 2018-08-20 Last updated: 2019-03-25
Ahmad, W., Olsson, R. & Sjöström, M. (2017). Interpreting Plenoptic Images as Multi-View Sequences for Improved Compression.
Open this publication in new window or tab >>Interpreting Plenoptic Images as Multi-View Sequences for Improved Compression
2017 (English)Data set, Primary data
Abstract [en]

The paper is written in the response to ICIP 2017, Grand challenge on plenoptic image compression. The input image format and compression rates set out by the competition are followed to estimate the results.

Keywords
Light field, plenoptic, MV-HEVC
Identifiers
urn:nbn:se:miun:diva-30740 (URN)
Available from: 2017-05-17 Created: 2017-05-17 Last updated: 2018-05-15
Ahmad, W., Olsson, R. & Sjöström, M. (2017). Interpreting Plenoptic Images as Multi-View Sequences for Improved Compression. In: ICIP 2017: . Paper presented at 24TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), Beijing, China 17-20 September 2017 (pp. 4557-4561). IEEE
Open this publication in new window or tab >>Interpreting Plenoptic Images as Multi-View Sequences for Improved Compression
2017 (English)In: ICIP 2017, IEEE, 2017, p. 4557-4561Conference paper, Published paper (Refereed)
Abstract [en]

Over the last decade, advancements in optical devices have made it possible for new novel image acquisition technologies to appear. Angular information for each spatial point is acquired in addition to the spatial information of the scene that enables 3D scene reconstruction and various post-processing effects. Current generation of plenoptic cameras spatially multiplex the angular information, which implies an increase in image resolution to retain the level of spatial information gathered by conventional cameras. In this work, the resulting plenoptic image is interpreted as a multi-view sequence that is efficiently compressed using the multi-view extension of high efficiency video coding (MV-HEVC). A novel two dimensional weighted prediction and rate allocation scheme is proposed to adopt the HEVC compression structure to the plenoptic image properties. The proposed coding approach is a response to ICIP 2017 Grand Challenge: Light field Image Coding. The proposed scheme outperforms all ICME contestants, and improves on the JPEG-anchor of ICME with an average PSNR gain of 7.5 dB and the HEVC-anchor of ICIP 2017 Grand Challenge with an average PSNR gain of 2.4 dB.

Place, publisher, year, edition, pages
IEEE, 2017
Keywords
Light field, plenoptic, MV-HEVC
Identifiers
urn:nbn:se:miun:diva-31455 (URN)10.1109/ICIP.2017.8297145 (DOI)000428410704138 ()2-s2.0-85045337163 (Scopus ID)978-1-5090-2175-8 (ISBN)
Conference
24TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), Beijing, China 17-20 September 2017
Note

Accepted paper.

Available from: 2017-08-22 Created: 2017-08-22 Last updated: 2018-05-15Bibliographically approved
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