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Panos Nasiopoulos

Researcher at University of British Columbia

Publications -  289
Citations -  3997

Panos Nasiopoulos is an academic researcher from University of British Columbia. The author has contributed to research in topics: Data compression & Video quality. The author has an hindex of 27, co-authored 271 publications receiving 3706 citations. Previous affiliations of Panos Nasiopoulos include Vancouver Community College & Dolby Laboratories.

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HEVC: The New Gold Standard for Video Compression

TL;DR: The limitations of current technologies prompted the International Standards Organization/International Electrotechnical Commission Moving Picture Experts Group (MPEG) and International Telecommunication Union-Telecommunication Standardization Sector Video Coding Experts group (VCEG) to establish the JCT-VC, with the objective to develop a new high-performance video coding standard.
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HEVC: The New Gold Standard for Video Compression: How Does HEVC Compare with H.264/AVC?

TL;DR: In this paper, the Joint Collaborative Team on Video Coding (JCT-VC) was established with the objective to develop a new high-performance video coding standard for mobile applications.
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Optimizing a Tone Curve for Backward-Compatible High Dynamic Range Image and Video Compression

TL;DR: It is shown that the appropriate choice of a tone-mapping operator (TMO) can significantly improve the reconstructed HDR quality and a statistical model is developed that approximates the distortion resulting from the combined processes of tone- mapping and compression.
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The Effect of Frame Rate on 3D Video Quality and Bitrate

TL;DR: In this paper, the relationship between 3D quality and bitrate at different frame rates was investigated. But the authors focused on the case of 2D video and not for 3D.
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Symmetry-Based Scalable Lossless Compression of 3D Medical Image Data

TL;DR: A modified version of the embedded block coder with optimized truncation (EBCOT), tailored according to the characteristics of the data, encodes the residual data generated after prediction to provide resolution and quality scalability.