High-order image subsampling using feedforward artificial neural networks

TitleHigh-order image subsampling using feedforward artificial neural networks
Publication TypeJournal Article
Year of Publication2001
AuthorsDumitras, A., and F. Kossentini
JournalIEEE Transactions on Image Processing
Volume10
Pagination427–435
ISSN1057-7149
Abstract

We propose a method for high-order image subsampling using feedforward artificial neural networks (FANNs). In our method, the high-order subsampling process is decomposed into a sequence of first-order subsampling stages. The first stage employs a tridiagonally symmetrical FANN, which is obtained by applying the design algorithm introduced in [1], The second stage employs a small fully connected FANN. The algorithm used to train both FANNs employs information about local edges (extracted using pattern matching) to perform effective subsampling of both high detail and smooth image areas. We show that our multistage first-order subsampling method achieves excellent speed-performance tradeoffs, and it consistently outperforms traditional lowpass filtering and subsampling methods both subjectively and objectively.

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