Abstract The adaptive local threshold algorithm is described in this paper. It has the same quality as Sauvola and is as fast as global threshold methods. The adaptive local threshold calculation is independent of the operator window size. It combines the advantages of Wiener filter prior processing, the integral images, and local threshold calculation.... The adaptive local threshold algorithm is described in this paper. It has the same quality as Sauvola and is as fast as global threshold methods. The adaptive local threshold calculation is independent of the operator window size. It combines the advantages of Wiener filter prior processing, the integral images, and local threshold calculation. Read More Read Less

Abstract In this paper, we attempt to review some of the most commonly used directional transforms in terms of their use in image coding, as well as some recommendations for improving their integration into full compression algorithms in the future. We compare DDCTs, DWHTs, DDWTs and others to each other based on image quality and execution time as well as memory... In this paper, we attempt to review some of the most commonly used directional transforms in terms of their use in image coding, as well as some recommendations for improving their integration into full compression algorithms in the future. We compare DDCTs, DWHTs, DDWTs and others to each other based on image quality and execution time as well as memory efficiency when used for image compression. These transforms are even more efficient when used with some spectral coefficient rearrangement, as suggested for further discussion. Read More Read Less

Abstract Nowadays, the demand for risk response is increasing in countries worldwide, leading to the development of emergency-related industries as strategic emerging sectors. However, the emergency logistics industry is facing increasingly critical distribution issues. This study applies K-means clustering analysis to convert multiple distribution centers into multiple single distribution center problems. It then compares and analyzes the vehicle routing model with... Nowadays, the demand for risk response is increasing in countries worldwide, leading to the development of emergency-related industries as strategic emerging sectors. However, the emergency logistics industry is facing increasingly critical distribution issues. This study applies K-means clustering analysis to convert multiple distribution centers into multiple single distribution center problems. It then compares and analyzes the vehicle routing model with time windows for emergency logistics delivery in multiple distribution centers using guided local search(GLS), taboo search (TS), and simulated annealing (SA) algorithm. The results demonstrate that the GLS algorithm outperformed both the SA and TS algorithm in optimizing emergency logistics delivery paths for multiple distribution centers. The GLS algorithm proved to be more effective in solving this problem. This study not only confirms the contemporary value of emergency logistics distribution problems but also offers practical insights into optimizing emergency logistics distribution paths in multiple distribution centers. Read More Read Less