Question

Which of the following transform is best suited for spatial filtering, edge detection, feature extraction, data compression, pattern recognition, speech recognition, image compression and texture analysis?

(a) wavelet transform

(b) laplace transform

(c) fourier transform

(d) short time fourier transform

I have been asked this question in exam.

Asked question is from The Main Amplifier and Driver Stage topic in chapter Recording System of Biomedical Instrumentation

Answer 1

The correct answer is (a) wavelet transform

The best explanation: The wavelet transform has very good time resolution at high frequencies and good frequency resolution at low frequencies. In biomedical engineering, wavelet transform have been widely used in many research areas including spatial filtering, edge detection, feature extraction, data compression, pattern recognition, speech recognition, image compression and texture analysis. Wavelets are a relatively new signal processing method. A wavelet transform is almost always implemented as a bank of filters that decompose a signal into multiple signal bands. It separates and retains the signal features in one or a few of these bands.