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Locally Adaptive DCT Filtering for Signal-Dependent Noise Removal

BROWSE_DETAIL_TITLE_ALTERNATE: Locally Adaptive DCT Filtering for Signal-Dependent Noise Removal

BROWSE_DETAIL_CREATION_DATE: 27-07-2009

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BROWSE_DETAIL_TYPE: Article

BROWSE_DETAIL_PUBLISH_STATE: Published

BROWSE_DETAIL_FORMAT: PDF Document

BROWSE_DETAIL_LANG: English

BROWSE_DETAIL_CREATORS: Öktem, Ruşen (Co-Author),

BROWSE_DETAIL_CONTRIBUTERS:

BROWSE_DETAIL_DOI: 10.1155/2007/42472

BROWSE_DETAIL_URL: http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2007/42472

BROWSE_DETAIL_IDENTIFIER_OTHER: http://acikarsiv.atilim.edu.tr/browse/9/manuscript.pdf

BROWSE_DETAIL_SOURCE: Yazar


BROWSE_DETAIL_PUBLICATION_NAME: EURASIP Journal on Advances in Signal Processing BROWSE_DETAIL_PUBLICATION_DATE: 27-07-2009


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BROWSE_DETAIL_TAB_KEYWORDS Gürültü arındırma, ayrık kosinüs dönüşümü, çarpımsal gürültü, yerel uyarlamalı süzgeçler
Denoising, dct, film-grain noise, multiplicative noise, locally adaptive filters
BROWSE_DETAIL_TAB_ABSTRACT
This work addresses the problem of signal dependent noise removal in images. An adaptive nonlinear filtering approach in the orthogonal transform domain is proposed and analyzed for several typical noise environments in the DCT domain. Being applied locally, i.e., within a window of small support, DCT is expected to approximate the Karhunen-Loeve decorrelating transform, which enables effective suppression of noise components. The detail preservation ability of the filter allowing not to destroy any useful content in images is especially emphasized and considered. A local adaptive DCT filtering for the two cases: when signal dependent noise can be and cannot be mapped into additive uncorrelated noise with homomorphic transform, is formulated. Although the main issue is signal dependent and pure multiplicative noise, the proposed filtering approach is also found to be competing with the state of the art methods on pure additive noise corrupted images.
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BROWSE_DETAIL_TAB_RIGHTS Yazar
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