VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
PicSOM—content-based image retrieval with self-organizing maps
Pattern Recognition Letters - Selected papers from the 11th scandinavian conference on image analysis
A Method of Remote Sensing Image Retrieval Based on ROI
ICITA '05 Proceedings of the Third International Conference on Information Technology and Applications (ICITA'05) Volume 2 - Volume 02
Copula-based statistical models for multicomponent image retrieval in the wavelet transform domain
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
| Hi-index | 0.00 |
In most current image retrieval systems, the retrieval process is performed using similarity strategies applied on certain features in the image. This paper presents a novel method for multispectral image retrieval. The proposed method starts with calculation of two features and then it uses Principal Component Analysis (PCA) to extract principal components of the feature values. Later on, feature values of each image are exhibited by a linear combination of these principal components. In the proposed approach, two effective weight vectors are calculated for each image in the system. These two weight vectors are used efficiently in radiance and texture based retrieval process. The proposed method was performed and tested on a set of LANDSAT multispectral images from variant sceneries. Experimental results show the superior performance of this approach.