Object recognition based on moment (or algebraic) invariants
Geometric invariance in computer vision
Content-Based Video Indexing and Retrieval
IEEE MultiMedia
Efficient and effective querying by image content
Journal of Intelligent Information Systems - Special issue: advances in visual information management systems
Multimedia Systems - Special issue on content-based retrieval
IEEE Spectrum
The Illumination-Invariant Recognition of 3D Objects Using Local Color Invariants
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Visual Information Management System for the Interactive Retrieval of Faces
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning to Perceive Objects for Autonomous Navigation
Autonomous Robots
Illumination Invariant Recognition of Color Texture Using Correlation and Covariance Functions
EMMCVPR '01 Proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Color Image Registration under Illumination Changes
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Affine illumination compensation for multispectral images
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
A hybrid computational model for an automated image descriptor for visually impaired users
Computers in Human Behavior
Affine illumination compensation on hyperspectral/multiangular remote sensing images
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part II
The invariance properties of chromatic characteristics
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
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We present a set of algorithms and a search strategy for the robust content-based retrieval of multispectral satellite images. Since the property of interest in these images is usually the physical characteristics of ground cover, we use representations and methods that are invariant to illumination and atmospheric conditions. The representations and algorithms are derived for this application from a physical model for the formation of multispectral satellite images. The use of several representations and algorithms is necessary to interpret the diversity of physical and geometric structure in these images. Algorithms are used that exploit multispectral distributions, multispectral spatial structure, and labeled classes. The performance of the system is demonstrated on a large set of multispectral satellite images taken over different areas of the United States under different illumination and atmospheric conditions.