Low-delay random view access in multi-view coding using a bit-rate adaptive downsampling approach

In this paper, a new multi-view coding (MVC) scheme is proposed and evaluated. The scheme offers improved low-delay view random access capability and at the same time comparable compression performance with respect to the reference multi-view coding scheme currently used. The proposed scheme uses the concept of multiple-resolution view coding, exploiting the trade-off between quantization distortion and downsampling distortion at changing bit-rates, which in turn provides improved coding efficiency. Bi-predictive (B) coded views, used in the conventional MVC method, are replaced with predictive coded downscaled views, reducing the view dependency in a multi-view set and hence reducing the random view access delay, but preserving the compression performance at the same time. Results show that the proposed method reduces the view random access delay in a MVC system significantly, but has a similar objective and subjective performance with the conventional MVC method

Combined Industry, Space and Earth Science Data Compression Workshop

The sixth annual Space and Earth Science Data Compression Workshop and the third annual Data Compression Industry Workshop were held as a single combined workshop. The workshop was held April 4, 1996 in Snowbird, Utah in conjunction with the 1996 IEEE Data Compression Conference, which was held at the same location March 31 - April 3, 1996. The Space and Earth Science Data Compression sessions seek to explore opportunities for data compression to enhance the collection, analysis, and retrieval of space and earth science data. Of particular interest is data compression research that is integrated into, or has the potential to be integrated into, a particular space or earth science data information system. Preference is given to data compression research that takes into account the scien- tist's data requirements, and the constraints imposed by the data collection, transmission, distribution and archival systems

Image Processing Using FPGAs

This book presents a selection of papers representing current research on using field programmable gate arrays (FPGAs) for realising image processing algorithms. These papers are reprints of papers selected for a Special Issue of the Journal of Imaging on image processing using FPGAs. A diverse range of topics is covered, including parallel soft processors, memory management, image filters, segmentation, clustering, image analysis, and image compression. Applications include traffic sign recognition for autonomous driving, cell detection for histopathology, and video compression. Collectively, they represent the current state-of-the-art on image processing using FPGAs

深層学習に基づく画像圧縮と品質評価

早大学位記番号:新8427早稲田大

Mobile graphics: SIGGRAPH Asia 2017 course

Peer ReviewedPostprint (published version