A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Fast Parallel Algorithm for Blind Estimation of Noise Variance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of noise in images: an evaluation
CVGIP: Graphical Models and Image Processing
Image processing through multiscale analysis and measurementnoise modeling
Statistics and Computing
Thresholding for Change Detection
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Differential approximation of the 2-D Laplace operator for edge detection in digital images
ICCCI'10 Proceedings of the Second international conference on Computational collective intelligence: technologies and applications - Volume Part III
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One of the significant problems in digital signal processing is the filtering and reduction of undesired interference. Due to the abundance of methods and algorithms for processing signals characterized by complexity and effectiveness of removing noise from a signal, depending on the character and level of noise, it is difficult to choose the most effective method. So long as there is specific knowledge or grounds for certain assumptions as to the nature and form of the noise, it is possible to select the appropriate filtering method so as to ensure optimum quality. This chapter describes several methods for estimating the level of noise and presents a new method based on the properties of the smoothing filter.