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Florida Institute of Technology

2004

Packet loss

Articles 1 - 2 of 2

Full-Text Articles in Engineering

Layered Unequal Loss Protection For Image Transmission Over Packet Loss Channels With Delay Constraints, Jianfei Cai, Xiangjun Li, Chang Wen Chen Oct 2004

Layered Unequal Loss Protection For Image Transmission Over Packet Loss Channels With Delay Constraints, Jianfei Cai, Xiangjun Li, Chang Wen Chen

Electrical Engineering and Computer Science Faculty Publications

In the case of high bit rate image transmission or having lots of packets, the FEC (forward error correction) encoding and decoding processes in the ULP (unequal loss protection) based schemes should be applied to individual packet groups instead of all the packets in order to avoid long processing delay. In this paper, we propose a layered ULP (L-ULP) scheme for fast and efficient FEC allocations among different packet groups and also within each packet group. The numerical results show that the proposed L-ULP scheme is quite promising for fast image transmission over packet loss networks.


Layered Unequal Loss Protection For Progressive Image Transmission Over Packet Loss Channels, Jianfei Cai, Xiangjun Li, Chang Wen Chen Jan 2004

Layered Unequal Loss Protection For Progressive Image Transmission Over Packet Loss Channels, Jianfei Cai, Xiangjun Li, Chang Wen Chen

Electrical Engineering and Computer Science Faculty Publications

In the past, many schemes have been proposed for progressive image transmission using unequal error protection (UEP) or unequal loss protection (ULP). However, most existing UEP/ULP schemes do not consider the minimum image quality requirement and usually have high computation complexity. In this paper, we propose a layered ULP (L-ULP) scheme for progressive image transmission over packet loss channels, which is able to solve the mentioned problems of existing ULP schemes by smartly choosing the layers. The numerical results show that the proposed L-ULP scheme is quite promising for fast image transmission over packet loss networks.