E. Adelson and P. Burt. Image data compression with the Laplacian pyramid. Proc. Patt. Recog. Info. Proc. Conf., pages 218--223, 1981.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....we wish to estimate or about which we wish to reason reside at the finest scale only. The coarser scale variables in such a case might simply represent decompositions of the finest scale variables into coarser scale components e.g. as in the use of wavelet decompositions or Laplacian pyramid [6, 47] representations of images. In other problems some of these coarser scale variables may be measured directly, as occurs in problems in which we wish to fuse data sets collected at di#ering resolutions. More generally the coarser scale variables may or may not be directly observed and may or may ....

E. Adelson and P. Burt. Image data compression with the Laplacian pyramid. Proc. Patt. Recog. Info. Proc. Conf., pages 218--223, 1981.

....and 5) We would now like to see how well this generalizes to arbitrary non linearities. A common technique in digital forging is to splice together signals in such a way that the seam is not perceptually salient. A pair of fractal signals were seamlessly spliced together using a Laplacian pyramid [7]. Each signal, x 1 (n) and x 2 (n) containing 8192 samples is first decomposed into a seven level Laplacian pyramid. A new pyramid is constructed by combining, at each pyramid level, the left half of x 1 (n) with the right half of x 2 (n) This new pyramid is then collapsed yielding the ....

E.H. Adelson and P.J. Burt. Image data compression with the Laplacian pyramid. In Proceedings of the conference on pattern recognition and image processing, pages 218--223, Dallas, TX, 1981. 9

....intensive Monte Carlo methods, like the version of the Metropolis algorithm proposed by Geman and Geman (1984) 2 Robert D. Nowak Multiscale (or multiresolution) techniques have been another popular and successful approach to many image analysis problems. Beginning with the seminal work of Adelson and Burt (1981), multiscale image analysis has found application in a wide range of tasks, from low level image processing to high level machine vision, and today, it is the basis for most state of the art image compression schemes. One of the advantages of the multiscale approach is its computational ....

Adelson, E. and Burt, P. (1981). Image data compression with the Laplacian pyramid. In Proc. Patt. Recog. Info. Proc. Conf., pages 218--223, Dallas, TX.

....homography may suffice, or a set of local homographies may be required. 2.3 Wide baseline stereo matching algorithm The algorithm consists of 3 main steps: 1. Automatically generate a (set of local) planar homographies. A global homography may be computed by standard pyramid search techniques [1, 9]. Often a similarity transformation suffices. Local (scene dependent) homographies may be computed using matching techniques similiar to those used in model based recognition [14] For example, using feature focus [3] to identify and match distinctive image features. In [13] four line groupings ....

E.H. Adelson and P.J. Burt. Image data compression with the laplacian pyramid. In PRIP81, pages 218--223, 1981.

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