Blurred kernel inversion method for blurred retouching images based on blurred deformation Riemann measure
A fuzzy kernel and Gaussian fuzzy kernel technology, applied in image enhancement, image data processing, instruments, etc., can solve the problems of trust crisis, reduce the credibility of digital media, and defraud the public.
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[0020] The technical scheme of the present invention is described in detail below in conjunction with accompanying drawing:
[0021] As a two-dimensional signal, an image can be represented in multiple transform domains, such as frequency domain (Fourier transform domain), Laplace domain, etc. The essence of Gaussian blur is image filtering. The Gaussian kernel function (normal distribution) is used to calculate the blur matrix, and the blur matrix is convolved with the source image to perform blurring. The blur operation can be expressed in the time domain as the convolution of the source image I(x,y) and the Gaussian blur kernel function G(x,y,δ), as shown in the following formula.
[0022] I blur (x,y)=I(x,y)*G(x,y,δ)
[0023] In the formula δ is the standard deviation of the normal distribution over the Gaussian kernel (referred to as the Gaussian blur kernel), and I blur (x,y) is the blurred retouched image, * is the convolution operation.
[0024] Let f be the R→...
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