L0 NORM OPTIMIZATION IN SAR IMAGE RECONSTRUCTION BASED ON SPARSE DECOMPOSITION

dc.contributor.authorЛазаров, Андон
dc.contributor.authorМинчев, Димитър
dc.date.accessioned2025-04-25T07:27:02Z
dc.date.issued2015
dc.description.abstractSynthetic Aperture Radar SAR) image reconstruction algorithms based sparse decomposition is considered. The linear frequency modulated (LFM) signal reflected from the scene, relief of the Earth surface is presented as matrix multiplication of three matrices: azimuth Inverse Discrete Fourier Transform (IDFT) matrix, image matrix and range IDFT matrix. L0 norm optimization image reconstruction procedure is applied over reduced number of measurements defined by randomly generated azimuth and range sensing matrix. The geometry of the scene is described by standard Matlab „peaks” function. Results of numerical experiments are provided.
dc.identifier.isbn978-619-7126-11-2
dc.identifier.urihttp://research.bfu.bg:4000/handle/123456789/2409
dc.language.isoen
dc.publisherБургаски свободен университет
dc.relation.ispartofseries2015
dc.subjectSAR
dc.subjectCompressed Sensing
dc.subjectl0 norm optimization
dc.subjectSparse Decomposition
dc.titleL0 NORM OPTIMIZATION IN SAR IMAGE RECONSTRUCTION BASED ON SPARSE DECOMPOSITION
dc.typeArticle

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