A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Characterization of Signals from Multiscale Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge characterization using normalized edge detector
CVGIP: Graphical Models and Image Processing
Linear Time Euclidean Distance Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Classified and Comparative Study of Edge Detection Algorithms
ITCC '02 Proceedings of the International Conference on Information Technology: Coding and Computing
Digital Image Processing Using MATLAB
Digital Image Processing Using MATLAB
ITNG '07 Proceedings of the International Conference on Information Technology
Edge and Curve Detection for Visual Scene Analysis
IEEE Transactions on Computers
Optimal threshold selection algorithm in edge detection based on wavelet transform
Image and Vision Computing
Analysis of multiscale products for step detection and estimation
IEEE Transactions on Information Theory
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A major dilemma in edge detections is the choice of optimum threshold which lacks generality. The problem is further amplified by the presence of false edges in the image due to noise. Addressing this dilemma the paper presents a novel technique by exploiting scale correlation with in wavelet subband for two dimensional signals with a view to retain structural information. The image is decomposed by dyadic wavelet transform up to 4th level through multilevel wavelet decomposition. The detail coefficients in concordant bands are multiplied after interpolation and then synthesized. Quartic root of resultant product yields edge map of the image coupled with noise suppression. Experimental results reveal that the proposed algorithm outperforms the classical edge detectors for real, synthetic and noisy images while it is simpler to implement.