Abstract
In this chapter, we become familiar with image analysis and processing. We learn definition and computation of two of the most popular 2D orthogonal image transformations, the 2D discrete Fourier transform (DFT) and 2D discrete cosine transform (DCT). We see how to use them for image filtering in frequency domain. Next, we find out the definition of 2D convolution of matrices and their usage for image filtering, i.e. calculation of local weighted mean values of image pixels. We learn 2D filter weights, the most frequently used for image smoothing (de-noising) and edge detection (masks of Sobel, Prewitt, Roberts, Laplacian). We become also familiar of some non-linear image processing with median and morphological filters (erosion, dilatation). In this chapter, principles of 2D wavelet transform of an image using pair of wavelet low- and high-pass filter are presented in an image processing example/exercise in an image processing example/exercise. Basics of JPEG standard (compression of still pictures) and MPEG standard (compression of moving pictures, i.e., movies) are summarized. Finally, example of image watermarking is shown.
Living in an epoch of pictures: only short message, visual icon, funny animoi, please!
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14 January 2022
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Zieliński, T.P. (2021). Image Processing. In: Starting Digital Signal Processing in Telecommunication Engineering. Textbooks in Telecommunication Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-49256-4_16
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DOI: https://doi.org/10.1007/978-3-030-49256-4_16
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