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Method and device for parallel processing of images

  • US 9,020,297 B2
  • Filed: 12/15/2011
  • Issued: 04/28/2015
  • Est. Priority Date: 12/17/2010
  • Status: Active Grant
First Claim
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1. A method configured for parallel computation for obtaining a first plurality of difference images and a number, n, of subsequent plurality of difference images, said method comprising:

  • a. Obtaining a first plurality of difference images from an original image defined by a plurality of pixels, the first plurality of difference images obtained by;

    i. Providing a plurality of blurring convolution functions, each of said blurring functions providing increasing degree of blurring of said original image upon convolution of said original image;

    ii. Establishing a plurality of difference convolution functions, Dif, by calculating a difference between any two of said blurring convolution functions, each of said two blurring convolution functions providing different degrees of blurring of said original image upon convolution of said original image; and

    iii. Calculating a plurality of difference images from said original image, by convolving each of said difference convolution functions, Dif, with said original image to obtain difference images,b. Obtaining a first down sampling anti-aliasing convolution function, DAcon(l), by convolving said plurality of blurring functions with a down sampling function and an anti-aliasing function;

    c. When n is larger than 1, obtaining additional down sampling anti-aliasing convolution function(s), DAcon(t), by convolving the previous down sampling antialiasing convolution function, DAcon(t-l), with said plurality of blurring functions, a down sampling function and an anti-aliasing function, beginning this step c with t =2, and repeating this step while increasing t with unitary increments until t reaches n;

    d. Convolving all of the down sampling anti-aliasing convolution functions, DAcon, with said original image to obtain an image(x) for each down sampling antialiasing convolution function DAcon(x);

    e. Obtaining the n subsequent pluralities of difference images, obtaining each plurality(x) from each image(x),wherein said blurring convolution functions are Gaussian.

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