This study proposes an effective method for repairing honeycomb artifacts by analyzing generational mechanisms and the related characteristics of these honeycomb artifacts based on the honeycomb artifacts in images collected using a fiber bundle imaging system. According to the distribution characteristics of honeycomb artifacts in the image, the original image was first divided into several sub-images by a splitting method to reduce the honeycomb artifact's image width. Then, a sliding window with a certain size was used to repair the honeycomb artifacts. Subsequently, the pixels located in the area of honeycomb artifacts were screened out of the sliding window according to the designed adaptive threshold mechanism, after which we calculated the pixel value difference and Euclidean distance between the pixel and another with the largest pixel value in the window to obtain the adaptive compensation coefficient for pixel repair, leading to a transverse of the sliding window and repair of the whole sub-image. Hence, an original image was finally formed with restored sub-images and vice versa. Based on the test results, the proposed method has a better performance, as shown by the objective evaluation index, indicating that it will repair the honeycomb artifacts in images better than the previously established honeycomb artifact restoration algorithms.