Uniqueness of the Gaussian Kernel for Scale-Space Filtering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multiresolution Hierarchical Approach to Image Segmentation Based on Intensity Extrema
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ten lectures on wavelets
An overview of morphological filtering
Circuits, Systems, and Signal Processing - Special issue: median and morphological filters
Scale-Space Properties of the Multiscale Morphological Dilation-Erosion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image processing and data analysis: the multiscale approach
Image processing and data analysis: the multiscale approach
Connections for sets and functions
Fundamenta Informaticae - Special issue on mathematical morphology
Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
International Journal of Computer Vision - Joint special issue on image analysis
Wavelets for Computer Graphics: A Primer, Part 1
IEEE Computer Graphics and Applications
Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
Morphological scale-space with application to three-dimensional object recognition
Morphological scale-space with application to three-dimensional object recognition
Levelings, Image Simplification Filters for Segmentation
Journal of Mathematical Imaging and Vision
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Multiscale Fourier descriptors for defect image retrieval
Pattern Recognition Letters
Flat zones filtering, connected operators, and filters by reconstruction
IEEE Transactions on Image Processing
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Multiscale approaches have been largely considered in several signal processing applications. They play an important role when designing automatic methods to cope with real world measurements where, in most of the cases, there is no prior information about which would be the appropriate scale. The basic idea behind a multiscale analysis is to embed the original signal into a family of derived signals, thus allowing the analysis of different representation levels and, further, the choice of the ones exhibiting the interest features. This paper presents a brief survey of two broadly used multiscale formulations, namely, wavelets and scale-space filtering. We present the basic definitions and some possible applications of these approaches in image processing.