Skip to Main content Skip to Navigation
Conference papers


Abstract : Hyperspectral images acquired by remote sensing systems are generally degraded by noise and can be sometimes more severely degraded by blur. In this study, we address the semi-blind restoration of the degraded images component-wise, according to a sequential scheme. We propose a new component-wise semi-blind method for estimating effectively and accurately both the blur and the corresponding latent image. To prove applicability and higher efficiency of the proposed method, we compare it against the method it originates from. Our attention is mainly paid to the objective analysis (via l(1)-norm) of the estimation error accuracy. The tests are performed on a synthetic hyperspectral image. This image has been successively degraded with eight real blurs taken from the literature, each of a different support size. Conclusions, practical recommendations and perspectives are drawn from the results experimentally obtained.
Document type :
Conference papers
Complete list of metadata
Contributor : Laurent Jonchère Connect in order to contact the contributor
Submitted on : Thursday, February 14, 2019 - 11:25:53 AM
Last modification on : Monday, January 24, 2022 - 1:53:43 PM


  • HAL Id : hal-02018915, version 1


Mo Zhang, B. Vozel, K. Chehdi, Mykhail Uss, Sergey Abramov, et al.. HYPERSPECTRAL IMAGE RESTORATION BASED ON SALIENT EDGES. 38th IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Jul 2018, Valencia, Spain. ⟨hal-02018915⟩



Les métriques sont temporairement indisponibles