Leonid Bilevich

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Convolution and correlation are very basic image processing operations with numerous applications ranging from image restoration to target detection to image resampling and geometrical transformation. In real time applications, the crucial issue is the processing speed, which implies mandatory use of algorithms with the lowest possible computational(More)
A new DCT-based algorithm for signal and image scaling by arbitrary factor is presented. The algorithm is virtually free of boundary effects and implements the discrete sinc-interpolation, which preserves the spectral content of the signal, and therefore is free from interpolation errors. Being implemented through the fast FFT-type DCT algorithm, the(More)
Image scaling is a frequent operation in video processing for optical metrology. In the paper, results of comparative study of computational complexity of different algorithms for scaling digital images with arbitrary scaling factors are presented and discussed. The following algorithms were compared: different types of spatial domain processing algorithms(More)
A general framework is presented for recursive computation of image local statistics in sliding window of almost arbitrary shape with “per-pixel” computational complexity substantially lower than the window size. As special cases, recursive algorithms are described for computing image local statistics such as local mean, local variance, local kurtosis,(More)
A new fast DCT-based algorithm for accurate image arbitrary scaling and rotation is described. The algorithm is free from boundary effects characteristic for FFT-based algorithm and ensures perfect interpolation with no interpolation errors. The algorithm is compared with other available algorithms in terms of the interpolation accuracy, computational(More)
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