In this paper we propose a unified variational image editing model. It interprets image editing as a variational problem concerning the adaptive adjustments to the zero- and first-derivatives of the images which corre...In this paper we propose a unified variational image editing model. It interprets image editing as a variational problem concerning the adaptive adjustments to the zero- and first-derivatives of the images which correspond to the color and gradient items. By varying the definition domain of each of the two items as well as applying diverse operators, the new model is capable of tackling a variety of image editing tasks. It achieves visually better seamless image cloning effects than existing approaches. It also induces a new and efficient solution to adjusting the color of an image interactively and locally. Other image editing tasks such as stylized processing, local illumination enhancement and image sharpening, can be accomplished within the unified variational framework. Experimental results verify the high flexibility and efficiency of the proposed model.展开更多
基金A preliminary version of this paper appeared in Proc. Pacific Graphics 2005, Macao. This work is partially supported by the National Basic Research 973 Program of China （Grant No. 2002CB312100）, the National Natural Science Foundation of China （Grant No. 60403038）, the National Natural Science Foundation of China for Innovative Research Groups （Grant No. 60021201）.
文摘In this paper we propose a unified variational image editing model. It interprets image editing as a variational problem concerning the adaptive adjustments to the zero- and first-derivatives of the images which correspond to the color and gradient items. By varying the definition domain of each of the two items as well as applying diverse operators, the new model is capable of tackling a variety of image editing tasks. It achieves visually better seamless image cloning effects than existing approaches. It also induces a new and efficient solution to adjusting the color of an image interactively and locally. Other image editing tasks such as stylized processing, local illumination enhancement and image sharpening, can be accomplished within the unified variational framework. Experimental results verify the high flexibility and efficiency of the proposed model.
