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Debargha Mukherjee

Researcher at Google

Publications -  208
Citations -  4397

Debargha Mukherjee is an academic researcher from Google. The author has contributed to research in topics: Codec & Encoder. The author has an hindex of 33, co-authored 203 publications receiving 4087 citations. Previous affiliations of Debargha Mukherjee include University of California & University of California, Santa Barbara.

Papers
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Journal ArticleDOI

Rate-distortion optimized mode selection for very low bit rate video coding and the emerging H.263 standard

TL;DR: An efficient solution is proposed in which the optimum combination of macroblock modes and the associated mode parameters are jointly selected so as to minimize the overall distortion for a given bit-rate budget, and is successfully applied to the emerging H.263 video coding standard.
Proceedings ArticleDOI

The latest open-source video codec VP9 - An overview and preliminary results

TL;DR: A brief technical overview of VP9 is provided along with comparisons with other state-of-the-art video codecs H.264/AVC and HEVC on standard test sets and results show VP9 to be quite competitive with mainstream state of theart codecs.
Patent

Method for embedding and extracting digital data in images and video

TL;DR: In this article, a discrete wavelet transform is employed for embedding gray scale images which can be as great as 25% of the host image data, and a control parameter is used that can be tailored to either hiding or watermarking purposes, and is robust to operations such as JPEG compression.
Journal ArticleDOI

A Technical Overview of VP9—The Latest Open-Source Video Codec

TL;DR: A brief technical overview of the coding tools included in VP9, along with coding performance comparisons with other state-of-the-art video codecs—namely, H.264/AVC and HEVC—on standard test sets are provided.
Journal ArticleDOI

Optimal adaptation decision-taking for terminal and network quality-of-service

TL;DR: The concepts behind metadata and constraint specifications that act as interfaces to the decision-taking component of an adaptation engine in MPEG-21 Part 7 are presented, universal methods based on pattern search are shown to process the information in the tools to make decisions, and some adaptation use cases where these tools can be used.