Contribution to a conference proceedings/Contribution to a book

FZJ-2015-00479

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Using Channel Representations in Regularization Terms - A Case Study on Image Diffusion

Heinemann, C. (Corresponding Author) ; Åström, F. ; Baravdish, G. ; Krajsek, K.FZJ* ; Felsberg, M. ; Scharr, H.FZJ*

2014
SCITEPRESS - Science and and Technology Publications

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Please use a persistent id in citations: doi:10.5220/0004667500480055

Abstract: In this work we propose a novel non-linear diffusion filtering approach for images based on their channel representation. To derive the diffusion update scheme we formulate a novel energy functional using a soft-histogram representation of image pixel neighborhoods obtained from the channel encoding. The resulting Euler-Lagrange equation yields a non-linear robust diffusion scheme with additional weighting terms stemming from the channel representation which steer the diffusion process. We apply this novel energy formulation to image reconstruction problems, showing good performance in the presence of mixtures of Gaussian and impulse-like noise, e.g. missing data. In denoising experiments of common scalar-valued images our approach performs competitive compared to other diffusion schemes as well as state-of-the-art denoising methods for the considered noise types.

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Contributing Institute(s):

1. Pflanzenwissenschaften (IBG-2)

Research Program(s):

1. 89582 - Plant Science (POF2-89582) (POF2-89582)

Appears in the scientific report 2014

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