Instant Edit Propagation on Images Based on Bilateral Grid

The ability to quickly and intuitively edit digital content has become increasingly important in our everyday life. However, existing edit propagation methods for editing digital images are typically based on optimization with high computational cost for large inputs. Moreover, existing edit propagation methods are generally inefficient and highly time-consuming. Accordingly, to improve edit efficiency, this paper proposes a novel edit propagation method using a bilateral grid, which can achieve instant propagation of sparse image edits. Firstly, given an input image with user interactions, we resample each of its pixels into a regularly sampled bilateral grid, which facilitates efficient mapping from an image to the bilateral space. As a result, all pixels with the same feature information (color, coordinates) are clustered to the same grid, which can achieve the goal of reducing both the amount of image data processing and the cost of calculation. We then reformulate the propagation as a function of the interpolation problem in bilateral space, which is solved very efficiently using radial basis functions. Experimental results show that our method improves the efficiency of color editing, making it faster than existing edit approaches, and results in excellent edited images with high quality.