A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal Edge Detection using Expansion Matching and Restoration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine vision
Minimal Surfaces Based Object Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Edge Enhancer for Supervised Edge Enhancement from Noisy Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bivariate shrinkage functions for wavelet-based denoising exploiting interscale dependency
IEEE Transactions on Signal Processing
Analysis of multiresolution image denoising schemes using generalized Gaussian and complexity priors
IEEE Transactions on Information Theory
De-noising by soft-thresholding
IEEE Transactions on Information Theory
Adaptive wavelet thresholding for image denoising and compression
IEEE Transactions on Image Processing
On optimal linear filtering for edge detection
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Omnidirectional edge detection
Computer Vision and Image Understanding
FPGA-based fuzzy PK controller and image processing system for small-sized humanoid robot
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Original paper: Real time feature extraction and Standard Cutting Models fitting in grape leaves
Computers and Electronics in Agriculture
Review article: Edge and line oriented contour detection: State of the art
Image and Vision Computing
No-reference image quality assessment using structural activity
Signal Processing
Differential operator in seizure detection
Computers in Biology and Medicine
Improving reversible histogram based data hiding schemes with an image preprocessing method
Proceedings of International Conference on Advances in Mobile Computing & Multimedia
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Laplacian operator is a second derivative operator often used in edge detection. Compared with the first derivative-based edge detectors such as Sobel operator, the Laplacian operator may yield better results in edge localization. Unfortunately, the Laplacian operator is very sensitive to noise. In this paper, based on the Laplacian operator, a model is introduced for making some edge detectors. Also, the optimal threshold is introduced for obtaining a Maximum a Posteriori (MAP) estimate of edges.