Compact support kernels based time-frequency distributions: Performance evaluation

This paper presents two new time-frequency distributions based on kernels with compact support (KCS) namely the separable CB (SCB) and the polynomial CB (PCB) TFDs. The implementation of these distributions follows the method developed for the Cheriet-Belouchrani CB TFD. The performance of this family of TFDs is compared to the most known quadratic distributions through tests on multi-component signals with linear and nonlinear frequency modulations (FMs) considering the noise effects as well. Comparisons are based on the evaluation of an objective criterion namely the Boashash-Sucic's normalized instantaneous resolution performance measure that allows to provide the optimized TFD using a specific methodology. In all presented examples, the KCS TFDs have been shown to have a significant interference mitigation, with the component energy concentration around their respective instantaneous frequency laws being well preserved giving high resolution measure values.

[1]  Mohamed Cheriet,et al.  KCS-new kernel family with compact support in scale space: formulation and impact , 2000, IEEE Trans. Image Process..

[2]  A. Belouchrani,et al.  On the use of a new compact support kernel in time frequency analysis , 2001, Proceedings of the 11th IEEE Signal Processing Workshop on Statistical Signal Processing (Cat. No.01TH8563).

[3]  Boualem Boashash,et al.  Resolution measure criteria for the objective assessment of the performance of quadratic time-frequency distributions , 2003, IEEE Trans. Signal Process..

[4]  Mohamed Cheriet,et al.  SKCS-new kernel family with compact support , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[5]  Mohamed Cheriet,et al.  PKCS: A Polynomial Kernel Family With Compact Support for Scale- Space Image Processing , 2007, IEEE Transactions on Image Processing.