document: Four-point wavelets and their applications Multiresolution analysis -LRB- MRA -RRB- and wavelets provide useful and efficient tools for representing functions at multiple levels of details . Wavelet representations have been used in a broad range of applications , including image compression , physical simulation and numerical analysis . In this paper , the authors construct a new class of wavelets , called four-point wavelets , based on an interpolatory four-point subdivision scheme . They are of local support , symmetric and stable . The analysis and synthesis algorithms have linear time complexity . Depending on different weight parameters w , the scaling functions and wavelets generated by the four-point subdivision scheme are of different degrees of smoothness . Therefore the user can select better wavelets relevant to the practice among the classes of wavelets . The authors apply the four-point wavelets in signal compression . The results show that the four-point wavelets behave much better than B-spline wavelets in many situations
doc_bio_tags: O O O O O B I O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O B I O B I O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O B I O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O
extractive_keyphrases: multiresolution analysis wavelet representations image compression physical simulation numerical analysis linear time complexity weight parameters scaling functions
abstractive_keyphrases: four-point wavelets interpolatory four-point subdivision scheme b-spline wavelets