Abstract
Most of existing focus measures are calculated by using the luminance information of source images while the chrominance information are ignored. In this paper, we first propose a new focus measure called quaternion morphological gradient for extracting the saliency feature of color images, which is derived based on the quaternion representation of color images and a proper ranking function. Then, the quaternion morphological gradients are used to produce initial decision maps. After that, the final decision maps are estimated by using the globally optimal weight maps obtained by the improved KNN matting algorithm. Finally, a weighted-sum strategy is used to construct the fused image. To boost the robustness of matting results, the pseudo depth information of source image is added into the feature vector of KNN matting. The experimental results validate the superiority of our method compared with the state-of-the-art algorithms both in visual perception and objective metrics.
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Liu, W., Zheng, Z., Wang, Z. (2021). Color Multi-focus Image Fusion Using Quaternion Morphological Gradient and Improved KNN Matting. In: Peng, Y., Hu, SM., Gabbouj, M., Zhou, K., Elad, M., Xu, K. (eds) Image and Graphics. ICIG 2021. Lecture Notes in Computer Science(), vol 12888. Springer, Cham. https://doi.org/10.1007/978-3-030-87355-4_43
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