Edge Detection Method Using Wavelet Transform Modulus Maxima

The edge detection method based on wavelet transform modulus maxima demonstrates significant advantages compared to conventional approaches. In this methodology, the signal first undergoes wavelet transformation using functions like 'cwt' or 'dwt' in signal processing libraries. The algorithm then detects modulus maximum points in the wavelet transform coefficients through local extremum analysis across different scales. By extracting these maxima points using thresholding techniques and connectivity analysis, the method effectively captures edge information of the signal. Compared to traditional edge detection methods like Sobel or Canny operators, this wavelet-based approach provides superior performance in handling noise sensitivity and achieving higher localization accuracy through its multi-resolution characteristics. The implementation typically involves scale-space analysis where edges correspond to modulus maxima lines that persist across multiple scales, making this a more advanced edge extraction technique for complex signal processing applications.