Abstract
Super resolution is a technique to obtain high resolution images from several degraded low-resolution images. This has got attention in the research society because of its wide use in many fields of science and technology. Even though many methods exist for super resolution, adaptive regularization method is preferred because of its simplicity and the constraints used to get better image restoration result. In this paper first adaptive algorithm is considered to restore better edge and texture of image. Further Genetic algorithm is used to smooth the noise and better frequency addition into the image to get an optimum super resolution image.
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Panda, S.S., Jena, G., Sahu, S.K. (2015). Image Super Resolution Reconstruction Using Iterative Adaptive Regularization Method and Genetic Algorithm. In: Jain, L., Behera, H., Mandal, J., Mohapatra, D. (eds) Computational Intelligence in Data Mining - Volume 2. Smart Innovation, Systems and Technologies, vol 32. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2208-8_62
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DOI: https://doi.org/10.1007/978-81-322-2208-8_62
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