A fast O(N) multiresolution polygonal approximation algorithm for GPS trajectory simplification

Recent advances in geopositioning mobile phones have made it possible for users to collect a large number of GPS trajectories by recording their location information. However, these mobile phones with built-in GPS devices usually record far more data than needed, which brings about both heavy data storage and a computationally expensive burden in the rendering process for a Web browser. To address this practical problem, we present a fast polygonal approximation algorithm in 2-D space for the GPS trajectory simplification under the so-called integral square synchronous distance error criterion in a linear time complexity. The underlying algorithm is designed and implemented using a bottom-up multiresolution method, where the input of polygonal approximation in the coarser resolution is the polygonal curve achieved in the finer resolution. For each resolution (map scale), priority-queue structure is exploited in graph construction to construct the initialized approximated curve. Once the polygonal curve is initialized, two fine-tune algorithms are employed in order to achieve the desirable quality level. Experimental results validated that the proposed algorithm is fast and achieves a better approximation result than the existing competitive methods.     

Onboard low-complexity compression of solar stereo images

We propose an adaptive distributed compression solution using particle filtering that tracks correlation, as well as performing disparity estimation, at the decoder side. The proposed algorithm is tested on the stereo solar images captured by the twin satellites system of NASA's Solar TErrestrial RElations Observatory (STEREO) project. Our experimental results show improved compression performance w.r.t. to a benchmark compression scheme, accurate correlation estimation by our proposed particle-based belief propagation algorithm, and significant peak signal-to-noise ratio improvement over traditional separate bit-plane decoding without dynamic correlation and disparity estimation.     

Riverbed: a novel user-steered image segmentation method based on optimum boundary tracking

This paper presents an optimum user-steered boundary tracking approach for image segmentation, which simulates the behavior of water flowing through a riverbed. The riverbed approach was devised using the image foresting transform with a never-exploited connectivity function. We analyze its properties in the derived image graphs and discuss its theoretical relation with other popular methods such as live wire and graph cuts. Several experiments show that riverbed can significantly reduce the number of user interactions (anchor points), as compared to live wire for objects with complex shapes. This paper also includes a discussion about how to combine different methods in order to take advantage of their complementary strengths.     

红枣醋发酵过程中醋酸发酵条件的优化

旨在采用液态静止表面发酵法,通过正交实验对红枣醋的醋酸发酵过程进行优化。得出醋酸发酵的最佳条件为温度32℃、酒精度6%、接种量10%、初始pH4.4,醋酸发酵结束后各项指标均符合国家食醋卫生标准,且红枣醋的Vc含量明显高于其他类型的果醋。