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Remote sensing image synthesis

2010 IEEE International Geoscience and Remote Sensing Symposium, 2010
For remote sensing data, the testing analysis tools is difficult since the ground-truth data are not available in many cases. To address this issue, a novel method for image synthesis is presented for use as a evaluation test-bed. Given the scale-dependent, non-stationary nature of remotely sensed data, a new modeling approach that combines a ...
Ying Liu 0010   +2 more
openaire   +1 more source

Remote Sensing Image Compression: A Review

2015 IEEE International Conference on Multimedia Big Data, 2015
With the increasing spatial and temporal resolutions of acquired remote sensing (RS) images, effective image compression is becoming more and more important. RS image compression technologies have been extensively studied in the past a few decades, and various algorithms have been developed accordingly.
Shichao Zhou   +5 more
openaire   +1 more source

Single Remote Sensing Image Dehazing

IEEE Geoscience and Remote Sensing Letters, 2014
Remote sensing images are widely used in various fields. However, they usually suffer from the poor contrast caused by haze. In this letter, we propose a simple, but effective, way to eliminate the haze effect on remote sensing images. Our work is based on the dark channel prior and a common haze imaging model.
Jiao Long   +3 more
openaire   +1 more source

Imaging Spectrometry for Earth Remote Sensing

Science, 1985
Imaging spectrometry, a new technique for the remote sensing of the earth, is now technically feasible from aircraft and spacecraft. The initial results show that remote, direct identification of surface materials on a picture-element basis can be accomplished by proper sampling of absorption features in the reflectance spectrum.
A F, Goetz   +3 more
openaire   +2 more sources

Digital Image Processing in Remote Sensing

2009 Tutorials of the XXII Brazilian Symposium on Computer Graphics and Image Processing, 2009
Imaging systems, particularly those on board satellites, provide a repetitive and consistent view of the earth that has been used in many remote sensing applications such as urban growth, deforestation and crop monitoring, weather prediction, land use mapping, land cover mapping and so on.
Leila Maria Garcia Fonseca   +2 more
openaire   +1 more source

Retrieving Images for Remote Sensing Applications

2006
A unique way in which content based image retrieval (CBIR) for remote sensing differs widely from traditional CBIR is the widespread occurrences of weak textures. The task of representing the weak textures becomes even more challenging especially if image properties like scale, illumination or the viewing geometry are not known.
SAWANT, N, CHANDRAN, S, MOHAN, BK
openaire   +1 more source

An Indexing Model of Remote Sensing Images

2004
This paper is concerned with the problem of indexing remote sensing images. This kind of images has a semantics mainly related to the image spectral properties. For these reasons the spectral properties can be considered as effective image descriptors.
Paola Carrara   +3 more
openaire   +1 more source

Compressed Sensing of a Remote Sensing Image Based on the Priors of the Reference Image

IEEE Geoscience and Remote Sensing Letters, 2015
Basic compressed-sensing algorithms for image reconstructions mainly deal with the computation of sparse regularization. Remote sensing applications often have multisource or multitemporal images whose different components are acquired separately. Therefore, this letter considers the reconstruction of a remote sensing image using an auxiliary image ...
Lizhe Wang 0001   +2 more
openaire   +1 more source

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