Remote Sensing Digital Image Analysis: An Introduction
Remote Sensing Digital Image Analysis: An Introduction
Computational Intelligence: An Introduction
Computational Intelligence: An Introduction
SIGGRAPH '78 Proceedings of the 5th annual conference on Computer graphics and interactive techniques
Journal of Visual Communication and Image Representation
Fractal image compression using visual-based particle swarm optimization
Image and Vision Computing
A GA-based movie-on-demand platform using multiple distributed servers
Multimedia Tools and Applications
Adaptive content-based music retrieval system
Multimedia Tools and Applications
Capture and fusion of 3d surface texture
Multimedia Tools and Applications
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Multispectral and multiresolution image fusion is important for many multimedia and remote sensing applications, such as video surveillance, medical imaging, and satellite imaging. For the commercial satellite "IKONOS," spatial resolutions of high-resolution panchromatic (PAN) and low-resolution multispectral (MS) satellite images are 1 m and 4 m, respectively. To cope with color distortion and blocking artifacts in fused images, in this study, a multispectral and multiresolution image fusion approach using PSO is proposed. The pixels of fused images in the training set are classified into several categories based on the characteristics of low-resolution MS images. Then, the smooth parameters of spatial and spectral responses between the high-resolution PAN and low-resolution MS images are determined by PSO. All the pixels within each category are normalized by its own smooth parameter so that color distortion and blocking artifacts can be greatly reduced. Based on the experimental results obtained in this study, the overall visual quality of the fused images by the proposed approach is better than that by three comparison approaches, whereas the correlation coefficients, 驴 PAN , for the fused images by the proposed approach are greater than that by three comparison approaches.