Multiresolution registration of remote sensing imagery by optimization of mutual information using a stochastic gradient
By Arlene A. Cole-Rhodes, Kisha L. Johnson, Jacqueline Le Moigne, Ilya Zavorin. IEEE Transactions on Image Processing, 2003
298 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Media Technology
View Paper: https://www.semanticscholar.org/paper/635bc8d4f6f2b6b3a5a905868198de3a374582ab
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Francesca Bovolo
- Nasreddine Taleb
- Jie Shan
- Lorenzo Bruzzone
- Joseph Ronsin
- Kidiyo Kpalma
- Qing Zhu
- Peter Reinartz
In Media Technology
- Francesca Bovolo
- Lorenzo Bruzzone
- Jie Shan
- Yuanxin Ye
- Peter Reinartz
- Turgay Çelik
- Gustau Camps-Valls
- Jon Atli Benediktsson
Citations in the corpus
- Fast and Robust Matching for Multimodal Remote Sensing Image Registration (2019, background): “As a result, MI can address nonlinear intensity differences to some extent [25].”
- An automatic image registration for applications in remote sensing (2005, methodology): “In this recent work, mutual information has been shown to be better suited for subpixel registration as it produces consistently sharper optimum peaks than correlation [13].”
- Mutual-Information-Based Registration of TerraSAR-X and Ikonos Imagery in Urban Areas (2010, background): “The similarity metric “S” that has been found useful for registration of SAR and optical images are, namely, mutualinformation (MI) and cluster-reward algorithms [5]–[9].”