• Corpus ID: 18462292

Parameter optimization of fast curvature based interpolation using genetic algorithm

@inproceedings{Haris2012ParameterOO,
  title={Parameter optimization of fast curvature based interpolation using genetic algorithm},
  author={Muhammad Haris and Kazuhito Sawase and Hajime Nobuhara and Takuya Sawada and Kazushi Kamijima and Widyanto M. Rahmat},
  year={2012}
}
An improvement of fast curvature based interpolation in image super resolution is proposed by using genetic algorithm optimization. The fast curvature based image super resolution requires low computation time, and it is suitable for real time video superresolution. This paper furthermore optimizes the parameters of FCBI based on genetic algorithm. Through the android device implementation, we confirm the quality of obtained super-resolution images by the proposed method is better than those of… 

References

SHOWING 1-10 OF 17 REFERENCES
Optimizing and Learning for Super-resolution
TLDR
It is demonstrated that superior estim ates are obtained by optimizing over both the registration and image, and the parameters of the edge preserving prior are learnt automatically from the data, rather than being set by trial and error.
A Fast Image Super-Resolution Algorithm Using an Adaptive Wiener Filter
  • R. Hardie
  • Environmental Science
    IEEE Transactions on Image Processing
  • 2007
TLDR
A computationally simple super-resolution algorithm using a type of adaptive Wiener filter that produces an improved resolution image from a sequence of low-resolution video frames with overlapping field of view and lends itself to parallel implementation.
Image and video upscaling from local self-examples
TLDR
The new method ability to produce high-quality resolution enhancement, its application to video sequences with no algorithmic modification, and its efficiency to perform real-time enhancement of low-resolution video standard into recent high-definition formats are demonstrated.
Genetic algorithms + data structures = evolution programs (3rd ed.)
TLDR
Genetic algorithms are a probabilistic search approach which are founded on the ideas of evolutionary processes and applicable to many hard optimization problems such as optimization of functions with linear and nonlinear constraints.
Genetic Algorithms in Search Optimization and Machine Learning
TLDR
This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Smartphone statistics and market share. http://www.email-marketing-reports.com/ wireless-mobile/smartphone-statistics.htm
  • Smartphone statistics and market share. http://www.email-marketing-reports.com/ wireless-mobile/smartphone-statistics.htm
  • 2012
New edge-directed interpolation
TLDR
Simulation results demonstrate that the new interpolation algorithm substantially improves the subjective quality of the interpolated images over conventional linear interpolation.
Genetic Algorithms + Data Structures = Evolution Program. Springler
  • 1996
IEEE Transaction on Image Processing
  • IEEE Transaction on Image Processing
...
...