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3,577
The "Independent Components" of Natural Scenes are Edge Filters
, 1997
"... It has previously been suggested that neurons with line and edge selectivities found in primary visual cortex of cats and monkeys form a sparse, distributed representation of natural scenes, and it has been reasoned that such responses should emerge from an unsupervised learning algorithm that attem ..."
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Cited by 617 (29 self)
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It has previously been suggested that neurons with line and edge selectivities found in primary visual cortex of cats and monkeys form a sparse, distributed representation of natural scenes, and it has been reasoned that such responses should emerge from an unsupervised learning algorithm
A combined corner and edge detector
- In Proc. of Fourth Alvey Vision Conference
, 1988
"... Consistency of image edge filtering is of prime importance for 3D interpretation of image sequences using feature tracking algorithms. To cater for image regions containing texture and isolated features, a combined corner and edge detector based on the local auto-correlation function is utilised, an ..."
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Cited by 2453 (2 self)
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Consistency of image edge filtering is of prime importance for 3D interpretation of image sequences using feature tracking algorithms. To cater for image regions containing texture and isolated features, a combined corner and edge detector based on the local auto-correlation function is utilised
An Optimized Macrobending-Fiber-Based Edge Filter
"... Abstract—An optimized all-fiber edge filter is developed, based on a one-turn macrobending bare fiber structure. The discrimi-nation range is 16.32 dB over a wavelength range from 1500 to 1600 nm, which can be employed for wavelength measurement ap-plications. It offers a simpler structure compared ..."
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Cited by 5 (5 self)
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Abstract—An optimized all-fiber edge filter is developed, based on a one-turn macrobending bare fiber structure. The discrimi-nation range is 16.32 dB over a wavelength range from 1500 to 1600 nm, which can be employed for wavelength measurement ap-plications. It offers a simpler structure compared
Bilateral Filtering for Gray and Color Images
, 1998
"... tomasi @ cs.stanford.edu Bilateral filtering smooths images while preserving edges, by means of a nonlinear combination of nearby image values. The method is noniterative, local, and sim-ple. It combines gray levels or colors based on both their geometric closeness and their photometric similariv, a ..."
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Cited by 1156 (2 self)
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tomasi @ cs.stanford.edu Bilateral filtering smooths images while preserving edges, by means of a nonlinear combination of nearby image values. The method is noniterative, local, and sim-ple. It combines gray levels or colors based on both their geometric closeness and their photometric similariv
Scale-space and edge detection using anisotropic diffusion
- IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1990
"... Abstract-The scale-space technique introduced by Witkin involves generating coarser resolution images by convolving the original image with a Gaussian kernel. This approach has a major drawback: it is difficult to obtain accurately the locations of the “semantically mean-ingful ” edges at coarse sca ..."
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Cited by 1887 (1 self)
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. The algorithm involves elementary, local operations replicated over the image making parallel hardware implementations feasible. Index Terms-Adaptive filtering, analog VLSI, edge detection, edge enhancement, nonlinear diffusion, nonlinear filtering, parallel algo-
A New BiGaussian Edge Filter
"... Abstract Edge detection has been the foremost step in image processing and computer vision, because an edge representation drastically reduces the amount of data to be processed. Although classical methods of edge detection like Sobel, Canny, etc. are simple to use but has a dilemma between noise re ..."
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removal and edge localization. If noise is to be removed by using a low pass filter then edges are blurred. However, if edges have to be preserved then noise severly corrupts the edge map. In this paper, we have proposed a new method of edge detection, BiGaussian edge Filter, which simultaneously removes
The maximal causes of natural scenes are edge filters
- NIPS
"... We study the application of a strongly non-linear generative model to image patches. As in standard approaches such as Sparse Coding or Independent Component Analysis, the model assumes a sparse prior with independent hidden variables. However, in the place where standard approaches use the sum to c ..."
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Cited by 13 (2 self)
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We study the application of a strongly non-linear generative model to image patches. As in standard approaches such as Sparse Coding or Independent Component Analysis, the model assumes a sparse prior with independent hidden variables. However, in the place where standard approaches use the sum to combine basis functions we use the maximum. To derive tractable approximations for parameter estimation we apply a novel approach based on variational Expectation Maximization. The derived learning algorithm can be applied to large-scale problems with hundreds of observed and hidden variables. Furthermore, we can infer all model parameters including observation noise and the degree of sparseness. In applications to image patches we find that Gabor-like basis functions are obtained. Gabor-like functions are thus not a feature exclusive to approaches assuming linear superposition. Quantitatively, the inferred basis functions show a large diversity of shapes with many strongly elongated and many circular symmetric functions. The distribution of basis function shapes reflects properties of simple cell receptive fields that are not reproduced by standard linear approaches. In the study of natural image statistics, the implications of using different superposition assumptions have so far not been investigated systematically because models with strong non-linearities have been found analytically and computationally challenging. The presented algorithm represents the first large-scale application of such an approach. 1
Fast Bilateral Filtering for the Display of High-Dynamic-Range Images
, 2002
"... We present a new technique for the display of high-dynamic-range images, which reduces the contrast while preserving detail. It is based on a two-scale decomposition of the image into a base layer, encoding large-scale variations, and a detail layer. Only the base layer has its contrast reduced, the ..."
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Cited by 453 (10 self)
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, thereby preserving detail. The base layer is obtained using an edge-preserving filter called the bilateral filter. This is a non-linear filter, where the weight of each pixel is computed using a Gaussian in the spatial domain multiplied by an influence function in the intensity domain that decreases
A Practical Guide to Wavelet Analysis
, 1998
"... A practical step-by-step guide to wavelet analysis is given, with examples taken from time series of the El Nio-- Southern Oscillation (ENSO). The guide includes a comparison to the windowed Fourier transform, the choice of an appropriate wavelet basis function, edge effects due to finite-length t ..."
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Cited by 869 (3 self)
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A practical step-by-step guide to wavelet analysis is given, with examples taken from time series of the El Nio-- Southern Oscillation (ENSO). The guide includes a comparison to the windowed Fourier transform, the choice of an appropriate wavelet basis function, edge effects due to finite
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multi-band Image Segmentation
- IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1996
"... We present a novel statistical and variational approach to image segmentation based on a new algorithm named region competition. This algorithm is derived by minimizing a generalized Bayes/MDL criterion using the variational principle. The algorithm is guaranteed to converge to a local minimum and c ..."
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Cited by 774 (20 self)
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, and the relationship to edge detection using filters. It is straightforward to generalize the algorithm to multiband segmentation and we demonstrate it on grey level images, color images and texture images. The novel color model allows us to eliminate intensity gradients and shadows, thereby obtaining segmentation
Results 1 - 10
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3,577