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This lecture covers the motivation behind multiresolution analysis in image processing, including adapting resolution strategies and the compact representation provided by wavelet transforms. It explains the Haar transform, multiscale signal representation, and the connection between wavelets and image pyramids. The lecture also delves into the two-scale relation sequence, wavelet decomposition, and the error pyramid. Additionally, it discusses the Haar expansion, filterbank formulation, and the connection between wavelets and image processing, as well as the basis functions and expansion coefficients in 2D. The presentation concludes with a summary of continuous/discrete image representation, interpolation, B-splines, multiscale image representation, and the concise representation of residues using wavelets.