1. A method of processing an image by a digital processor, comprising: calculating by the digital processor of a weighting coefficient w ij for each pixel i with multi-channel values represented by a vector z i and a neighboring pixel j with multi-channel values represented by a vector z j in the image based on a spatial location of the neighboring pixel by substituting in an expression for the weighting coefficient a term ∥z i −z j ∥ 2 with a conjugate norm in a form ∥•∥Q T Q or in a form ∥•∥Q T ΛQ, wherein each pixel is assigned a multi-channel value, and each pixel is connected locally to an adjacent pixel independent of the multi-channel value, wherein: Q is a matrix representation of an eigenvector that depends on a Laplacian matrix of a graph defined by pixels of the image; Λ is a matrix representation of an eigenvalue that depends on the Laplacian matrix; T in an exponent indicates a transposition of a matrix; and ∥•∥ indicates a norm of any expression represented by •; and generating for further processing a processed image by the digital processor using the weighting coefficients; and segmenting an object in the processed image using the weighting coefficients, wherein the weighting coefficient for each pixel and an adjacent pixel is determined in accordance with the following equation: w ij = exp ⁡ [ - ( z i - z j ) T ⁢ Q T ⁢ Λ ⁢ ⁢ Q ⁡ ( z i - z j ) σ 2 ] , wherein i indicates a pixel and j indicates a pixel, w ij represents the weighting coefficient between pixels i and j, z i represents a color vector of a pixel i, z j represents a color vector of a pixel j and σ is a free parameter.