Title :
Algorithms for adaptive transform edge detection
Author_Institution :
Information Syst. Inc., West Lafayette, IN
fDate :
8/1/1999 12:00:00 AM
Abstract :
Edge detection in grayscale digital images based on the locations of zero crossings has been investigated. Samples of the image are transformed using the discrete symmetric cosine transform (DSCT) and filtered using truncated time or frequency sampled forms of the Laplacian-of-Gaussian (LOG) filter. This article presents and evaluates adaptive block-based filtering procedures to localize edges based on discrete circular and real transforms. Measures of the signal-to-noise ratio (SNR) and edge localization are provided
Keywords :
adaptive filters; adaptive signal processing; discrete cosine transforms; edge detection; filtering theory; image sampling; DSCT; Laplacian-of-Gaussian filter; SNR measures; adaptive block-based filtering; adaptive transform edge detection; algorithms; discrete circular transform; discrete real transform; discrete symmetric cosine transform; edge localization; grayscale digital images; image samples; linear convolution; signal-to-noise ratio; truncated frequency sampled filter; truncated time filter; zero crossings location; Adaptive filters; Band pass filters; Convolution; Digital images; Discrete transforms; Filtering theory; Frequency; Image edge detection; Sampling methods; Signal to noise ratio;
Journal_Title :
Signal Processing, IEEE Transactions on
