M.A. Chaudhry, M.N. Jafri, M. Mufti, and M. Akbar (Pakistan)
Regularity, maximally flat, perfect reconstruction, bi-orthogonal wavelet bases, distinguishibility function.
In this paper, we propose a methodology for the optimal design of bi-orthogonal wavelet basis for maximum possible texture discrimination. The objective of this optimization process is to obtain maximum separation between local features of the texture image at different resolution scales. There are several applications which may not require reconstruction of signal from its transformed coefficients such as texture analysis, remote sensing, medical diagnostics etc. Therefore, for such applications, features are extracted at different frequency resolution scales and condition for perfect reconstruction can be relaxed. In this research work, we propose a methodology for the optimal design of bi-orthogonal wavelet bases. Our objective function is based on maximization of distinguishibility function involving the computation of finer details subject to some wavelet constraints. Classification results of optimized wavelet were compared with the existing maximally flat bi orthogonal wavelet families which shows that the results obtained are superior in terms of texture discrimination.
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