Contourlet Transform Implementation

This code implementation focuses on the contourlet transform, which extracts contourlets through polynomial fitting of one-dimensional signals. The implementation process begins with smoothing the original signal using appropriate window functions or averaging filters. Subsequently, the program performs a series of filtering operations using digital filters (possibly FIR or IIR filters) to enhance signal characteristics. The core algorithm then applies polynomial fitting to the smoothed signal, where the code likely utilizes least-squares polynomial regression to approximate signal contours. The implementation includes detailed analysis of contourlet features such as directional sensitivity and multi-scale decomposition properties, enabling users to better understand contourlet fundamentals and their applications in various signal processing domains. Overall, this program serves as a practical contourlet extraction tool suitable for multiple signal processing applications including image processing, biomedical signal analysis, and communication systems.