The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper proposes a novel unsupervised method based on primitive cluster sensitive hashing for fast and accurate image retrieval in large remote sensing (RS) archives. The proposed method consists of a three-steps algorithm. In the first step, each image in the archive is characterized by primitive clusters' descriptors. These descriptors are obtained through an unsupervised approach, which automatically...
This paper presents a novel system for the content based retrieval in remote sensing images based on the Bag of Spectral Values. In the proposed method, the spatial and spectral information contents of RS images are treated separately by parallel pipelines. Defining a novel spectral descriptor, the Bag of Spectral Values, this approach allows for a computationally efficient extraction of features...
This paper proposes a novel system for fast and accurate content based retrieval of hyperspectral images. The proposed system aims at retrieving hyperspectral images that have both similar spectral characteristics associated with specific materials and fractional abundances to the query image. It consists of two modules. The first module characterizes the query and the target hyperspectral images...
This paper presents a novel active learning (AL) method for retrieving remote sensing images from large archives. The proposed AL method defines an effective set of relevant and irrelevant images with regard to a query image by jointly evaluating three criteria: i) uncertainty, ii) diversity and iii) density of images in the archive. The proposed AL method assesses jointly the three criteria based...
This paper presents a novel active learning (AL) technique to drive relevance feedback in content based image retrieval (CBIR) from earth observation data archives. The proposed AL method aims at defining an effective set of relevant and irrelevant images with respect to the query image as small as possible. This is achieved on the basis of a joint evaluation of three criteria: i) uncertainty, ii)...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.