• Computer Science
  • Published 2018

Evaluation of super-resolution algorithm for detection and recognition of features from MODIS and OLI images at sub-pixel scale using Hopfield Neural Network

@inproceedings{Abarghooee2018EvaluationOS,
  title={Evaluation of super-resolution algorithm for detection and recognition of features from MODIS and OLI images at sub-pixel scale using Hopfield Neural Network},
  author={Mohammad Hosein Mehrzadeh Abarghooee and Ali S. Ardakani},
  year={2018}
}
Fuzzy classification techniques have been developed recently to estimate the class composition of image pixels, but their output provides no indication of how these classes are distributed spatially within the instantaneous field of view represented by the pixel. Super-resolution land-cover mapping is a promising technology for prediction of the spatial distribution of each land-cover class at the sub-pixel scale. This distribution is often determined based on the principle of spatial… CONTINUE READING

References

Publications referenced by this paper.
SHOWING 1-10 OF 32 REFERENCES

Super-resolution target identification from remotely sensed images using a Hopfield neural network

VIEW 6 EXCERPTS
HIGHLY INFLUENTIAL

Superresolution Land Cover Mapping With Multiscale Information by Fusing Local Smoothness Prior and Downscaled Coarse Fractions

  • Feng Ling, Yun Du, +4 authors Wenbo Li
  • Mathematics, Computer Science
  • IEEE Transactions on Geoscience and Remote Sensing
  • 2014
VIEW 2 EXCERPTS

Attraction-Repulsion Model-Based Subpixel Mapping of Multi-/Hyperspectral Imagery

VIEW 2 EXCERPTS