[IPOL announce] new article: Small Neural Networks can Denoise Image Textures Well: a Useful Complement to BM3D
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Tue Jan 19 22:28:13 CET 2016
A new article is available in IPOL: http://www.ipol.im/pub/art/2016/150/
Yi-Qing Wang,
Small Neural Networks can Denoise Image Textures Well: a Useful
Complement to BM3D,
Image Processing On Line, 6 (2016), pp. 1–7.
http://dx.doi.org/10.5201/ipol.2016.150
Abstract
Recent years have seen a surge of interest in deep neural networks
fueled by their successful applications in numerous image processing and
computer vision tasks. However, such applications typically come with
huge computational loads. In this article, we explore the possibility of
using small neural networks to denoise images. In particular, we present
SSaNN (Self-Similarity and Neural Networks), a denoising algorithm which
combines the strength of BM3D on large-scale structured patterns with
that of neural networks on small-scale texture content. This algorithm
is able to produce a better overall recovery than both BM3D and small
neural networks.
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