Abstract
Two methods for local adaptive two-dimensional processing of medical images are developed. In the first one the adaptation is based on the local information from the four neighborhood pixels of the processed image and the interpolation type is changed to zero or bilinear. In the second one the adaptive image halftoning is based on the generalized 2D LMS error-diffusion filter. An analysis of the quality of the processed images is made on the basis of the calculated PSNR, SNR, MSE and the subjective observation. The given experimental results from the simulation in MATLAB 6.5 environment of the developed algorithms, suggest that the effective use of local information contributes to minimize the processing error. The methods are extremely suitable for different types of images (for example: fingerprints, contour images, cartoons, medical signals, etc.). The methods have low computational complexity and are suitable for real-time applications.
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Acknowledgments
This work was supported by the Joint Research Project Bulgaria-Romania (2010–2012): “Electronic Health Records for the Next Generation Medical Decision Support in Romanian and Bulgarian National Healthcare Systems”, NextGenElectroMedSupport.
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Mironov, R. (2014). Adaptive Interpolation and Halftoning for Medical Images. In: Iantovics, B., Kountchev, R. (eds) Advanced Intelligent Computational Technologies and Decision Support Systems. Studies in Computational Intelligence, vol 486. Springer, Cham. https://doi.org/10.1007/978-3-319-00467-9_8
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DOI: https://doi.org/10.1007/978-3-319-00467-9_8
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