# Progressive Dynamic Registration Method for Tile Maps Based on Optimum Multi-Features
## 2 Literature Review
The Canny edge detection algorithm was proposed by [PERSON] [16] in 1986 and is still widely used today. The key to the Canny algorithm is to find the location in the image where the gray intensity changes most strongly. The algorithm first selects a certain Gaussian filter for smooth filtering to realize image denoising and then conducts nonpolar suppression and double-threshold screening to obtain the result. There are some other edge detection algorithms, such as ratio of exponential weighted average (ROEWA) [17], line segment detector (LSD) [18], and Gaussian-Gamma-shaped (GGS) bi-window [19], which are also widely used to extract edges from remote sensing images. [PERSON] et al. [20] proposed a registration method based on image feature lines in 2010, which first extracts image edges using the LoG operator, then obtains the main straight lines in the edge information using Hough transform, obtains the registration parameters by calculation, and finally realizes image registration. In 2011, [PERSON] et al. [21] used the Canny algorithm to extract the image edges to obtain the chain code in the image to solve the problem of not matching images under different wavelength channels in NIR ice detection. By comparing the angle and coordinate difference of the chain code, the image was rotated and panned to achieve image matching. In 2017, [PERSON] et al. [22] proposed a line segment-based image registration method. He used an improved Canny operator (Canny DIR) to detect edges, then extracted line segments from the edges. The algorithm was reliable and accurate on multimodal images. Aiming to improve the inaccurate and incomplete results when using a single image segmentation method for image segmentation, [PERSON] et al. [23] applied morphology to Canny edge detection to segment images. The completeness and accuracy of the results were improved after applying the method. [PERSON] et al. [24] proposed a high-speed feature extraction algorithm based on the block type classification algorithm to reduce the computational complexity of feature detection. He applied the proposed method to the Canny edge detection. After experimental verification, it could eliminate the latency of adaptive threshold value calculation. [PERSON] et al. [25] proposed a radar remote sensing image retrieval algorithm that was based on feature vector information. He used an improved Sobel operator to get the edge image. Then, the radar remote sensing image was analyzed from different angles, and the statistic was recorded as a feature-describing vector. Using the feature-describing vector of images can greatly reduce the retrieval time. The algorithms based on feature points with good stability and strong noise resistance have been widely used in image registration. The feature lines and feature surfaces are easily broken when extracted [26], resulting in incomplete feature lines. It is difficult to achieve a one-to-one correspondence between the two images, and the extraction process is more time-consuming, so it is less used. At this stage, there is no single feature- matching strategy that can solve all registration problems, and different methods should be chosen to register different images by combining their features in different scenarios. In some studies, multi-features are used in the registration process. [PERSON] et al. [27] proposed a region- and feature-based approach for medical image registration in 2018, which is a coarse-to-fine framework. In the coarse registration stage, the closed contours of the target are extracted for a fast initial transformation of the global range; in the fine registration stage, an accurate final transformation is achieved using the modified feature neighborhood and mutual information. [PERSON] et al. [28] proposed a method that combined feature points and feature lines for image registration. Firstly, he used LSD to extract the feature lines for coarse registration. Then, the Harris operator was used for fine registration.