Spatial Classification Using Fuzzy Membership Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Classification Method Using Stochastic Model that Reflects the Internal Structure of Mixels
SSPR '98/SPR '98 Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
Trimap segmentation for fast and user-friendly alpha matting
VLSM'05 Proceedings of the Third international conference on Variational, Geometric, and Level Set Methods in Computer Vision
Hi-index | 0.00 |
The mixel is a heterogeneous pixel that contains multiple constituents within a single pixel, and the statistical properties of a population of mixels can be characterized by the mixel distribution. Practically this model has a drawback that it cannot be represented in closed form, and prohibitive numerical computation is required for mixture density estimation problem. Our discovery however shows that the "moments" of the mixel distribution can be derived in closed form, and this solution brings about significant reduction of computation cost for mixture density estimation after slightly modifying a typical algorithm. We then show the experimental result on satellite imagery, and find out that the modified algorithm runs more than 20 times faster than our previous method, but suffers little deterioration in classification performance.