Taşmaz, HaciDemirel, HasanAnbarjafari, Gholamreza2025-02-242025-02-242012978-146730056-810.1109/SIU.2012.62044632-s2.0-84863425225https://doi.org/10.1109/SIU.2012.6204463https://hdl.handle.net/20.500.14440/5832012 20th Signal Processing and Communications Applications Conference -- SIU 2012 -- 18 April 2012 through 20 April 2012 -- Fethiye -- Mugla -- 90786This research work proposes a satellite image enhancement system consisting of image denoising and illumination enhancement technique based on dual tree complex wavelet transform (DT-CWT). The technique firstly decomposes the noisy input image into different frequency subbands by using DT-CWT and denoises these subbands by using local adaptive bivariate shrinkage function (LA-BSF) which assumes the dependency of subband detail coefficients. In LA-BSF, model parameters are estimated in a local neighborhood which results in improved denoising performance. Then the denoised image once more is decomposed into the different frequency subbands by using DT-CWT. The highest singular value of the low frequency subbands are used in order to enhance the illumination of the denoised image. Finally the image is reconstructed by applying the inverse DT-CWT (IDT-CWT). The experimental results show the superiority of the proposed method over the conventional and the state-of-art techniques. © 2012 IEEE.trinfo:eu-repo/semantics/closedAccessForestryIlluminationImage AnalysisTelecommunicationsForestryImage enhancementImage segmentationSignal processingBivariate shrinkagesDe-noisingDetail coefficientsDifferent frequencyDual-tree complex wavelet transformEnhancement techniquesInput imageLocal-adaptiveLow frequencyModel parametersSatellite imagesSingular valuesSubbandsImage denoisingConference ObjectN/A