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Book ChapterDOI

Performance evaluation of multiresolution methods in disparity estimation

30 Jun 2010-pp 496-504
TL;DR: This work is an effort to put different multiresolution methods together to highlight their expediency and suitability along with the comparison to get a better understanding of disparity estimation from stereo imagery.
Abstract: Disparity estimation from stereo imagery has gained substantial interest of research community from its commencement with the recent trend being the use of multiresolution methods. Existing multiresolution based methods are relatively independent and do not, in general, relate to a continuous progress in the research. As a result, the relative advantages and disadvantages of a particular multiresolution method in disparity estimation are hard to understand. Present work is an effort to put different multiresolution methods together to highlight their expediency and suitability along with the comparison to get a better understanding. Three different frameworks are used having different strengths and limitations followed by the comparison in the terms of time complexity, quality of matching and effect of different levels of decomposition. Qualitative and quantitative results have been provided for four types of standard multiresolution methods.

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Citations
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Journal ArticleDOI
TL;DR: The proposed transform inherits the excellent properties of MR-SVD along with its own unique features, which can be useful in many research areas, and is proposed to introduce randomness in the computing process based on parameters without which one can neither decompose nor reconstruct the data correctly.

17 citations


Cites background from "Performance evaluation of multireso..."

  • ...These applications include speaker recognition [14], speech signal enhancement [22], image compression [2,3], watermarking [1,13], stereo vision [15], fault diagnosis [23], image fusion [16] and other miscellaneous applications [10,19]....

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References
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Journal ArticleDOI
TL;DR: This paper has designed a stand-alone, flexible C++ implementation that enables the evaluation of individual components and that can easily be extended to include new algorithms.
Abstract: Stereo matching is one of the most active research areas in computer vision. While a large number of algorithms for stereo correspondence have been developed, relatively little work has been done on characterizing their performance. In this paper, we present a taxonomy of dense, two-frame stereo methods designed to assess the different components and design decisions made in individual stereo algorithms. Using this taxonomy, we compare existing stereo methods and present experiments evaluating the performance of many different variants. In order to establish a common software platform and a collection of data sets for easy evaluation, we have designed a stand-alone, flexible C++ implementation that enables the evaluation of individual components and that can be easily extended to include new algorithms. We have also produced several new multiframe stereo data sets with ground truth, and are making both the code and data sets available on the Web.

7,458 citations


"Performance evaluation of multireso..." refers methods in this paper

  • ...The well-known Middlebury datasets Tsukuba [ 9 ] and Cones [10] are used for generating comparative results....

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Journal ArticleDOI
TL;DR: A "true" two-dimensional transform that can capture the intrinsic geometrical structure that is key in visual information is pursued and it is shown that with parabolic scaling and sufficient directional vanishing moments, contourlets achieve the optimal approximation rate for piecewise smooth functions with discontinuities along twice continuously differentiable curves.
Abstract: The limitations of commonly used separable extensions of one-dimensional transforms, such as the Fourier and wavelet transforms, in capturing the geometry of image edges are well known. In this paper, we pursue a "true" two-dimensional transform that can capture the intrinsic geometrical structure that is key in visual information. The main challenge in exploring geometry in images comes from the discrete nature of the data. Thus, unlike other approaches, such as curvelets, that first develop a transform in the continuous domain and then discretize for sampled data, our approach starts with a discrete-domain construction and then studies its convergence to an expansion in the continuous domain. Specifically, we construct a discrete-domain multiresolution and multidirection expansion using nonseparable filter banks, in much the same way that wavelets were derived from filter banks. This construction results in a flexible multiresolution, local, and directional image expansion using contour segments, and, thus, it is named the contourlet transform. The discrete contourlet transform has a fast iterated filter bank algorithm that requires an order N operations for N-pixel images. Furthermore, we establish a precise link between the developed filter bank and the associated continuous-domain contourlet expansion via a directional multiresolution analysis framework. We show that with parabolic scaling and sufficient directional vanishing moments, contourlets achieve the optimal approximation rate for piecewise smooth functions with discontinuities along twice continuously differentiable curves. Finally, we show some numerical experiments demonstrating the potential of contourlets in several image processing applications.

3,948 citations


"Performance evaluation of multireso..." refers methods in this paper

  • ...A key feature in multidimensional signal being the directional features, Contourlet Transform (CONT) decomposes an image into several directional subband by combining the Laplacian pyramid with a directional filter at each scale [ 5 ]....

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Journal ArticleDOI
TL;DR: This paper describes two digital implementations of a new mathematical transform, namely, the second generation curvelet transform in two and three dimensions, based on unequally spaced fast Fourier transforms, while the second is based on the wrapping of specially selected Fourier samples.
Abstract: This paper describes two digital implementations of a new mathematical transform, namely, the second generation curvelet transform in two and three dimensions. The first digital transformation is based on unequally spaced fast Fourier transforms, while the second is based on the wrapping of specially selected Fourier samples. The two implementations essentially differ by the choice of spatial grid used to translate curvelets at each scale and angle. Both digital transformations return a table of digital curvelet coefficients indexed by a scale parameter, an orientation parameter, and a spatial location parameter. And both implementations are fast in the sense that they run in O(n^2 log n) flops for n by n Cartesian arrays; in addition, they are also invertible, with rapid inversion algorithms of about the same complexity. Our digital transformations improve upon earlier implementations—based upon the first generation of curvelets—in the sense that they are conceptually simpler, faster, and far less redundant. The software CurveLab, which implements both transforms presented in this paper, is available at http://www.curvelet.org.

2,603 citations


"Performance evaluation of multireso..." refers background or methods in this paper

  • ...For the implementation, Curvelets via Wrapping [ 2 ] has been used with the codes provided by the Curvelab....

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  • ...Curvelets are new multiscale representations that are better suited to objects with smooth curvatures [ 2 ]....

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Proceedings ArticleDOI
18 Jun 2003
TL;DR: A method for acquiring high-complexity stereo image pairs with pixel-accurate correspondence information using structured light that does not require the calibration of the light sources and yields registered disparity maps between all pairs of cameras and illumination projectors.
Abstract: Progress in stereo algorithm performance is quickly outpacing the ability of existing stereo data sets to discriminate among the best-performing algorithms, motivating the need for more challenging scenes with accurate ground truth information. This paper describes a method for acquiring high-complexity stereo image pairs with pixel-accurate correspondence information using structured light. Unlike traditional range-sensing approaches, our method does not require the calibration of the light sources and yields registered disparity maps between all pairs of cameras and illumination projectors. We present new stereo data sets acquired with our method and demonstrate their suitability for stereo algorithm evaluation. Our results are available at http://www.middlebury.edu/stereo/.

1,840 citations


"Performance evaluation of multireso..." refers methods in this paper

  • ...The well-known Middlebury datasets Tsukuba [9] and Cones [ 10 ] are used for generating comparative results....

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Journal ArticleDOI
01 Apr 1996
TL;DR: This tutorial describes major applications to multiresolution search, multiscale edge detection, and texture discrimination.
Abstract: Early on, computer vision researchers have realized that multiscale transforms are important to analyze the information content of images. The wavelet theory gives a stable mathematical foundation to understand the properties of such multiscale algorithms. This tutorial describes major applications to multiresolution search, multiscale edge detection, and texture discrimination.

354 citations


"Performance evaluation of multireso..." refers background in this paper

  • ...Wavelets are time limited functions that are localized in frequency [ 7 ]....

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  • ...A lot of research have been reported on wavelet based stereo estimation [3, 7 ,11]....

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