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3-D Mean-Separation-Type Short-Time DFT with Its Application to Moving-Image Denoising

Citation Author(s):
Takashi Komatsu, Ken Tyon, Takahiro Saito
Submitted by:
Takahiro Saito
Last updated:
13 September 2017 - 8:19pm
Document Type:
Poster
Document Year:
2017
Event:
Presenters:
Takahiro Saito
Paper Code:
TA-PB.3
 

Although for a still image the 2-D DFT and the 2-D DCT have similar properties to each other, for a moving-image sequence the 3-D DFT gets an advantage of representing the sequence more compactly over the 3-D DCT. Through the mathematical analysis of the 3-D DFT and the 3-D DCT based on a simple signal model of a moving-image sequence, this paper shows that the even symmetrization employed implicitly by the 3-D DCT may cause deterioration of representation efficiency and hence the 3-D DFT can achieve better representation efficiency than the 3-D DCT. In addition, to improve the suitability of the 3-D short-time DFT to processing of video signals which generally have significant local DC components carrying important structural information, this paper introduces a technique of local-mean-separation as a preprocess of the 3-D short-time DFT, thus to construct 3-D mean-separation-type ST-DFT; applies it to video denoising, and demonstrates its advantage over the existing 3-D transforms through experimental simulations of video denoising.

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