Aǧirliklandirilmiş Dalgacik Dönüşümü ile Pankeskinleştirme

Translated title of the contribution: Pansharpening via weighted additive wavelet transform

Nur Hüseyin Kaplan, Işin Erer

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

In additive wavelet transform (AWT) based classical pansharpening methods, the details of the panchromatic (PAN) image added to the multispectral (MS) image directly or by weighting after the detail extraction. In this paper, the details will be weighted during the detail extraction process. The details of the PAN image will be obtained by a weighted additive wavelet transform (WAWT). In order to achieve this aim, the range parameter of WAWT will be optimized for every image. The results obtained by the proposed method are compared with the classical AWT method, the context based method (CBD), and the enhanced CBD (ECB) method. It is observed that the proposed injection approach has better performance than the conventional weighted detail injection schemes.

Translated title of the contributionPansharpening via weighted additive wavelet transform
Original languageTurkish
Title of host publication2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages781-784
Number of pages4
ISBN (Electronic)9781509016792
DOIs
Publication statusPublished - 20 Jun 2016
Event24th Signal Processing and Communication Application Conference, SIU 2016 - Zonguldak, Turkey
Duration: 16 May 201619 May 2016

Publication series

Name2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings

Conference

Conference24th Signal Processing and Communication Application Conference, SIU 2016
Country/TerritoryTurkey
CityZonguldak
Period16/05/1619/05/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Fingerprint

Dive into the research topics of 'Pansharpening via weighted additive wavelet transform'. Together they form a unique fingerprint.

Cite this