article · IEEE Transactions on Image Processing · 2008
An Orientation-Selective Orthogonal Lapped Transform
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Abstract
A novel critically sampled orientation-selective orthogonal lapped transform called the lapped Hartley transform (LHT) is derived. In a first step, overlapping basis functions are generated by modulating basis functions of a 2-D block Hartley transform by a cosine wave. To achieve invertibility and orthogonality, an iterative filter is applied as prefilter in the analysis and as postfilter in the synthesis operation, respectively. Alternatively, filtering can be restricted to analysis or synthesis, ending up with a biorthogonal transform (LHT-PR, LHT-PO). A statistical analysis based on a 4000-image data base shows that the LHT and LHT-PO have better redundancy removal properties than other block or lapped transforms. Finally, image compression and noise removal examples are given, showing the advantages of the LHT especially in images containing oriented textures.
Cite this paper
Kunz, D. (2008). An Orientation-Selective Orthogonal Lapped Transform. IEEE Transactions on Image Processing, 17(8), 1313–1322. https://doi.org/10.1109/tip.2008.926160
Kunz, Dietmar. “An Orientation-Selective Orthogonal Lapped Transform.” IEEE Transactions on Image Processing, vol. 17, no. 8, 2008, pp. 1313–22, https://doi.org/10.1109/tip.2008.926160.
Kunz, Dietmar. 2008. “An Orientation-Selective Orthogonal Lapped Transform.” IEEE Transactions on Image Processing 17 (8): 1313–22. https://doi.org/10.1109/tip.2008.926160.
Kunz, D. (2008) ‘An Orientation-Selective Orthogonal Lapped Transform’, IEEE Transactions on Image Processing, 17(8), pp. 1313–1322. Available at: https://doi.org/10.1109/tip.2008.926160.
@article{kunz2008orientation,
title = {{An Orientation-Selective Orthogonal Lapped Transform}},
author = {Kunz, Dietmar},
journal = {IEEE Transactions on Image Processing},
volume = {17},
number = {8},
pages = {1313--1322},
year = {2008},
doi = {10.1109/tip.2008.926160}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.