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This paper proposes a novel model for contrast enhancement of RGB images. The average local contrast measure is increased within a variational framework which preserves the hue of the original image by coupling the channels. The user is enabled to intuitively control the level of the contrast as well as the scale of the enhanced details. Moreover, our model avoids large modifications of the original...
Bilateral filtering is a commonly used technique in image processing. However, being nonlinear, it is computationally expensive. The situation gets worse while the filter radius grows up. Several works have been proposed to accelerate the computation. Nevertheless, most techniques are tailored for grayscale image bilateral filtering or confined to specific kernel functions. In this paper, we propose...
In this paper, we consider a natural extension of the edge-preserving bilateral filter for vector-valued images. The direct computation of this non-linear filter is slow in practice. We demonstrate how a fast algorithm can be obtained by first approximating the Gaussian kernel of the bilateral filter using raised-cosines, and then using Monte Carlo sampling. We present simulation results on color...
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