Digital Signal Processing Applications
Jaideva C. Goswami, Andrew K. Chan · 2010
The 2D wavelet signal processing mainly involves image compression and target identification. Problem areas include noise reduction, signature identification, target detection, signal and image compression, and interference suppression. This chapter gives several examples to demonstrate the advantages and flexibility of using wavelets in signal and image processing. It discusses the extension of the wavelet algorithms to wavelet-packet algorithms and their 2D versions and then discusses various application examples. Thresholding is one of the most commonly used processing tools in wavelet signal processing. Edge detection is a discipline of great importance in digital image analysis. The majority of early breast cancers are indicated by the presence of one or more clusters of microcalcifications on a mammogram. Multicarrier modulation is the principle of transmitting data by dividing the data stream into several parallel bitstreams, each of which has a much lower bit rate. Controlled Vocabulary Terms data compression; digital signal processing; edge detection; wavelet transforms