An Accelerated Superpixel Generation Algorithm Based on 4-Labeled-Neighbors

Superpixels are perceptually meaningful atomic regions that could effectively improve efficiency of subsequent image processing tasks. Simple linear iterative clustering (SLIC) has been widely used for superpixel calculation due to outstanding performance. In this paper, we propose an accelerated SLIC superpixel generation algorithm using 4-labeled neighbor pixels called 4L-SLIC. The main idea of 4L-SLIC is that the labels are assigned to a portion of the pixels while the others that associated with certain cluster are restrained by adjacent four labeled pixels. In this way, the average number of distance calculated times of pixels are effectively reduced and the similarity between adjacent pixels ensures a better segmentation effect. The experimental results confirm that 4L-SLIC achieved a speed up of 25%–30% without declining accuracy sharply compared to SLIC. In contrast to the method published on CVIU 2016, 4L-SLIC has an acceptable increase in the cost of time, in the mean time, there is a significant ascension to the accuracy of the segmentation.