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The Design and Use of Steerable Filters
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1991
"... Oriented filters are useful in many early vision and image processing tasks. One often needs to apply the same filter, rotated to different angles under adaptive control, or wishes to calculate the filter response at various orientations. We present an efficient architecture to synthesize filters of ..."
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Cited by 851 (12 self)
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Oriented filters are useful in many early vision and image processing tasks. One often needs to apply the same filter, rotated to different angles under adaptive control, or wishes to calculate the filter response at various orientations. We present an efficient architecture to synthesize filters of arbitrary orientations from linear combinations of basis filters, allowing one to adaptively "steer" a filter to any orientation, and to determine analytically the filter output as a function of orientation.
PyramidBased Texture Analysis/Synthesis
, 1995
"... This paper describes a method for synthesizing images that match the texture appearanceof a given digitized sample. This synthesis is completely automatic and requires only the "target" texture as input. It allows generation of as much texture as desired so that any object can be covered. ..."
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Cited by 387 (0 self)
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This paper describes a method for synthesizing images that match the texture appearanceof a given digitized sample. This synthesis is completely automatic and requires only the "target" texture as input. It allows generation of as much texture as desired so that any object can be covered. It can be used to produce solid textures for creating textured 3d objects without the distortions inherent in texture mapping. It can also be used to synthesize texture mixtures, images that look a bit like each of several digitized samples. The approach is based on a model of human texture perception, and has potential to be a practically useful tool for graphics applications. 1 Introduction Computer renderings of objects with surface texture are more interesting and realistic than those without texture. Texture mapping [15] is a technique for adding the appearance of surface detail by wrapping or projecting a digitized texture image ontoa surface. Digitized textures can be obtained from a variety ...
Modeling the Joint Statistics of Images in the Wavelet Domain
 IN PROC SPIE, 44TH ANNUAL MEETING
, 1999
"... I describe a statistical model for natural photographic images, when decomposed in a multiscale wavelet basis. In particular, I examine both the marginal and pairwise joint histograms of wavelet coefficients at adjacent spatial locations, orientations, and spatial scales. Although the histograms ar ..."
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Cited by 97 (3 self)
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I describe a statistical model for natural photographic images, when decomposed in a multiscale wavelet basis. In particular, I examine both the marginal and pairwise joint histograms of wavelet coefficients at adjacent spatial locations, orientations, and spatial scales. Although the histograms are highly nonGaussian, they are nevertheless well described using fairly simple parameterized density models.
Adaptive Multidimensional Filtering
 LINKÖPING UNIVERSITY, SWEDEN
, 1992
"... This thesis contains a presentation and an analysis of adaptive filtering strategies for multidimensional data. The size, shape and orientation of the filter are signal controlled and thus adapted locally to each neighbourhood according to a predefined model. The filter is constructed as a linear we ..."
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Cited by 31 (0 self)
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This thesis contains a presentation and an analysis of adaptive filtering strategies for multidimensional data. The size, shape and orientation of the filter are signal controlled and thus adapted locally to each neighbourhood according to a predefined model. The filter is constructed as a linear weighting of fixed oriented bandpass filters having the same shape but different orientations. The adaptive filtering methods have been tested on both real data and synthesized test data in 2D, e.g. still images, 3D, e.g. image sequences or volumes, with good results. In 4D, e.g. volume sequences, the algorithm is given in its mathematical form. The weighting coefficients are given by the inner products of a tensor representing the local structure of the data and the tensors representing the orientation of the filters. The procedure and filter design in estimating the representation tensor are described. In 2D, the tensor contains information about the local energy, the optimal orientation and a certainty of the orientation. In 3D, the information in the tensor is the energy, the normal to the best fitting local plane and the tangent to the best fitting line, and certainties of these orientations. In the case of time sequences, a quantitative comparison of the proposed method and other (optical flow) algorithms is presented. The estimation of control information is made in different scales. There are two main reasons for this. A single filter has a particular limited pass band which may or may not be tuned to the different sized objects to describe. Second, size or scale is a descriptive feature in its own right. All of this requires the integration of measurements from different scales. The increasing interest in wavelet theory supports the idea that a multiresolution approach is necessary. Hence the resulting adaptive filter will adapt also in size and to different orientations in different scales.
Steerable Filters and Local Analysis of Image Structure
, 1992
"... Two paradigms for visual analysis are topdown, starting from highlevel models or information about the image, and bottomup, where little is assumed about the image or objects in it. We explore a local, bottomup approach to image analysis. We develop operators to identify and classify image junct ..."
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Cited by 28 (0 self)
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Two paradigms for visual analysis are topdown, starting from highlevel models or information about the image, and bottomup, where little is assumed about the image or objects in it. We explore a local, bottomup approach to image analysis. We develop operators to identify and classify image junctions, whichcontain important visual cues for identifying occlusion, transparency, and surface bends. Like the human visual system, we begin with the application of linear filters which are oriented in all possible directions. Wedevelop an efficientway to create an oriented filter of arbitrary orientation by describing it as a linear combination of basis filters. This approach to oriented filtering, which we call steerable filters, offers advantages for analysis as well as computation. We design a variety of steerable filters, including steerable quadrature pairs, which measure local energy. We show applications of these filters in orientation and texture analysis, and image representation and enhanc...
Image Denoising Using a Local Gaussian Scale Mixture Model in the Wavelet Domain
, 2000
"... The statistics of photographic images, when decomposed in a multiscale wavelet basis, exhibit striking nonGaussian behaviors. The joint densities of clusters of wavelet coefficients (corresponding to basis functions at nearby spatial positions, orientations and scales) are welldescribed as a Gauss ..."
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Cited by 24 (6 self)
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The statistics of photographic images, when decomposed in a multiscale wavelet basis, exhibit striking nonGaussian behaviors. The joint densities of clusters of wavelet coefficients (corresponding to basis functions at nearby spatial positions, orientations and scales) are welldescribed as a Gaussian scale mixture: a jointly Gaussian vector multiplied by a hidden scaling variable. We develop a maximum likelihood solution for estimating the hidden variable from an observation of the cluster of coefficients contaminated by additive Gaussian noise. The estimated hidden variable is then used to estimate the original noisefree coefficients. We demonstrate the power of this model through numerical simulations of image denoising.
Recognition of Surface Reflectance Properties from a Single Image under Unknown RealWorld Illumination
, 2001
"... This paper describes a machine vision system that classifies reflectance properties of surfaces such as metal, plastic, or paper, under unknown realworld illumination. We demonstrate performance of our algorithm for surfaces of arbitrary geometry. Reflectance estimation under arbitrary omnidirectio ..."
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Cited by 21 (1 self)
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This paper describes a machine vision system that classifies reflectance properties of surfaces such as metal, plastic, or paper, under unknown realworld illumination. We demonstrate performance of our algorithm for surfaces of arbitrary geometry. Reflectance estimation under arbitrary omnidirectional illumination proves highly underconstrained. Our reflectance estimation algorithm succeeds by learning relationships between surface reflectance and certain statistics computed from an observed image, which depend on statistical regularities in the spatial structure of realworld illumination. Although the algorithm assumes known geometry, its statistical nature makes it robust to inaccurate geometry estimates.
Qualityaware images
 IEEE Transactions on Image Processing
, 2006
"... Abstract — We propose the concept of qualityaware image, in which certain extracted features of the original (highquality) image are embedded into the image data as invisible hidden messages. When a distorted version of such an image is received, users can decode the hidden messages and use them t ..."
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Cited by 16 (3 self)
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Abstract — We propose the concept of qualityaware image, in which certain extracted features of the original (highquality) image are embedded into the image data as invisible hidden messages. When a distorted version of such an image is received, users can decode the hidden messages and use them to provide an objective measure of the quality of the distorted image. To demonstrate the idea, we build a practical qualityaware image encoding, decoding and quality analysis system 1, which employs 1) a novel reducedreference image quality assessment algorithm based on a statistical model of natural images, and 2) a previously developed quantization watermarkingbased data hiding technique in the wavelet transform domain. Index Terms — qualityaware image, image quality assessment, reducedreference image quality assessment, natural image statistics, generalized Gaussian density, information hiding, image watermarking, image communication I.
Surface Reflectance Estimation and Natural Illumination Statistics
 IN PROC. OF IEEE WORKSHOP ON STATISTICAL AND COMPUTATIONAL THEORIES OF VISION
, 2001
"... Humans recognize optical reflectance properties of surfaces such as metal, plastic, or paper from a single image without knowledge of illumination. We develop a machine vision system to perform similar recognition tasks automatically. Reflectance estimation under unknown, arbitrary illumination prov ..."
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Cited by 11 (4 self)
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Humans recognize optical reflectance properties of surfaces such as metal, plastic, or paper from a single image without knowledge of illumination. We develop a machine vision system to perform similar recognition tasks automatically. Reflectance estimation under unknown, arbitrary illumination proves highly underconstrained due to the variety of potential illumination distributions and surface reflectance properties. We have found that the spatial structure of realworld illumination possesses some of the statistical regularities observed in the natural image statistics literature. A human or computer vision system may be able to exploit this prior information to determine the most likely surface reflectance given an observed image. We develop an algorithm for reflectance classification under unknown realworld illumination, which learns relationships between surface reflectance and certain features (statistics) computed from a single observed image. We also develop an automatic feature selection method.