A Real-Time Cascaded Video Denoising Algorithm Using Intensity and Structure Tensor

Xin TAN  Yu LIU  Huaxin XIAO  Maojun ZHANG  

IEICE TRANSACTIONS on Information and Systems   Vol.E98-D   No.7   pp.1333-1342
Publication Date: 2015/07/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2014EDP7435
Type of Manuscript: PAPER
Category: Image Processing and Video Processing
cascaded framework,  change segmentation,  real-time capability,  structure tensor,  video denoising,  

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A cascaded video denoising method based on frame averaging is proposed in this paper. A novel segmentation approach using intensity and structure tensor is used for change compensation, which can effectively suppress noise while preserving the structure of an image. The cascaded framework solves the problem of noise residual caused by single-frame averaging. The classical Wiener filter is used for spatial denoising in changing areas. Our algorithm works in real-time on an FPGA, since it does not involve future frames. Experiments on standard grayscale videos for various noise levels demonstrate that the proposed method is competitive with current state-of-the-art video denoising algorithms on both peak signal-to-noise ratio and structural similarity evaluations, particularly when dealing with large-scale noise.