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Image decomposition consists of splitting an image into two or more components. One component is piecewise smooth and models object shapes. Another component consists of the texture in the image, possibly including some noise. Image decomposition is useful for a host of image processing tasks, e.g. texture segmentation and image inpainting. In this paper, we consider ways of improving both the speed and quality of image decomposition using the basic variational approach of Meyer (2001) by adding extra regularization terms. A measure of quality of image decomposition found in the literature Daubechies, I et al., (2004) is the absence of cartoon edges in the texture component of the decomposition. In this paper, we introduce a method called improved edge segregation image decomposition, which ensures this quality measure is high. When combined with active contour texture discrimination, improved results are obtained over conventional methods.