Name
Title | ||
|---|---|---|
Standard-Compliant Multiple Description Image Coding Based On Convolutional Neural Networks |
Abstract | ||
|---|---|---|
Multiple description (MD) coding is an attractive framework for robust information transmission over non-prioritized and unpredictable networks. In this paper, a novel MD image coding scheme is proposed based on convolutional neural networks (CNNs), which aims to improve the reconstructed quality of side and central decoders. For this purpose initially, a given image is encoded into two independent descriptions by sub-sampling. Such a design can make the proposed method compatible with the existing image coding standards. At the decoder, in order to achieve high-quality of side and central image reconstruction, three CNNs, including two side decoder sub-networks and one central decoder sub-network, are adopted into an end-to-end reconstruction framework. Experimental results show the improvement achieved by the proposed scheme in terms of both peak signal-to-noise ratio values and subjective quality. The proposed method demonstrates better rate central and side distortion performance. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1587/transinf.2018EDL8028 | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS |
Keywords | Field | DocType |
image coding, multiple description (MD) coding, convolutional neural network | Pattern recognition,Convolutional neural network,Computer science,Image coding,Artificial intelligence,Multiple description | Journal |
Volume | Issue | ISSN |
E101D | 10 | 1745-1361 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ting Zhang | 1 | 227 | 38.58 |
| Bai Huihui | 2 | 243 | 41.01 |
| Mengmeng Zhang | 3 | 115 | 24.91 |
| Yao Zhao | 4 | 1926 | 219.11 |