FANN-based video chrominance subsampling

TitleFANN-based video chrominance subsampling
Publication TypeConference Paper
Year of Publication1998
AuthorsDumitras, A., and F. Kossentini
Conference NameAcoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Pagination1077 -1080 vol.2
Date Publishedmay.
Keywordscomputational efficiency, FANN-based video chrominance subsampling, feedforward artificial neural networks, feedforward neural nets, image colour analysis, image sampling, memory requirement, multilayer perceptrons, video signal processing

In this paper, we present a video chrominance subsampling method using feedforward artificial neural networks (FANNs). Experimental results show that our method outperforms spatial subsampling obtained via low pass filtering and decimation both objectively and subjectively. Other advantages of our algorithm are computational efficiency and low memory requirements. Moreover, no pre- or post-processing is required by our method


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