Decolorization aims at converting color images into grayscale images while preserving their original contrast and color discriminability. In this paper, we introduce an original fusion-based decolorization approach. Our algorithm employs as inputs the three color channels R, G, and B, and an additional input related to the Helmholtz-Kohlrausch effect. To blend those inputs, we adopt a multiscale fusion strategy to prevent the artifacts arising from a pixel-wise application of weight maps and use several weight maps that respectively control saliency, exposure, and saturation. The new operator has been tested successfully on a large data set of both natural and synthetic images. It is competitive compared with modern optimization-based methods in terms of decolorized image visual quality while offering the advantage of being computationally simple, and temporally consistent when decolorizing video sequences.