33 results about "Fast marching method" patented technology

The invention relates to the technical field of wireless communication and particularly relates to a spatial characteristic estimation method based on a fast marching method. A signal transmitting source transmits a signal, a signal receiving node receives the signal, and the signal receiving node analyzes the received signal and extracts real transit time between the signal transmitting source and the signal receiving node. The fastest marching path between the transmitting source and the receiving node is searched in a coordinate system with the use of the fast marching method, simulation transit time between the transmitting source and the receiving node is calculated, and meanwhile, the simulation transit time is approached to the real transit time through iteration of an algebraic reconstruction method so as to obtain the spatial characteristics of each coordinate point on the fastest marching path. According to the invention, by making use of the ideas of the fast marching method, estimation and planning of a fast path in an environment are realized, and moreover, the spatial characteristics of a path are estimated by making full use of relevant TOF and speed distribution information acquired in path estimation so as to obtain an environment model, thus improving the accuracy of estimation on communication situation in an unknown environment.

The present invention provides a time-optimal route planning method based on an improved level set algorithm. The method comprises: 1, constructing a three-dimensional route planning environmental space; 2, initializing a level set function as a symbol distance function, and setting the AUV navigation starting point on a zero level set; 3, constructing a level set evolution equation considering the influence of the ocean current on the AUV navigation, and constructing a narrow band at the starting point and setting a prohibited area; 4, evolving a level set function according to the level set equation established in the step 3, and storing the zero level set interface of each time step length; 5, determining whether a target point is in the current narrow-band range or not; 6, reconfiguring the narrow band, and employing an improved fast marching method to reinitialize the level set function to be a symbol distance function; and 7, employing a back iterative equation, obtaining the time-optimal route of the AUV, and outputting an optimal route. Through adoption of an ocean current reanalysis database, the time-optimal route planning method based on the improved level set algorithm generates an ocean current field and fully considers the influence of the ocean current in the route planning to allow the planning route to have high practicality.

The invention discloses an improved high-efficiency automatic history fitting method for oil and gas reservoirs. The steps are as follows: S1. Obtain the hard data of the well point, and process the hard data of the well point to obtain several prior geological models. The prior geological model is regarded as a set; S2, based on the prior geological model, the fast marching method and the differential evolution algorithm are used to perform fitting calculation. By combining the fast marching method and the differential evolution algorithm, the technology of the present invention provides an efficient automatic history method for oil and gas reservoirs considering single-phase unstable seepage, which can quickly converge to the minimum value of the objective function, thereby completing automatic history fitting and solving the dependence The automatic history fitting process of conventional numerical simulation is time-consuming, which improves the efficiency of automatic fitting.

The invention provides a blood vessel extraction method for a live tumor angiogenesis image under an optical resolution photo-acoustic microscope (OR-PAM), and belongs to the field of image processing. First, a tumor angiogenesis image is preprocessed using a variety of enhanced algorithms, which enhances the contrast of small blood vessels effectively and reduces the influence of noise to the greatest degree. Then, a threshold is selected automatically to binaryze the image using an Otsu algorithm, which reduces the mis-classification probability. Finally, the centerline of a blood vessel is measured using a two-step fast marching method, so the calculated centerline can be located in the blood vessel more accurately. Blood vessel extraction using the traditional level set blood vessel extraction algorithm is too slow, while the running speed of the blood vessel extraction algorithm based on the fast marching method is increased greatly. Experimental results show that the method can be used to extract the blood vessel information of a tumor angiogenesis image more effectively, and has a good extraction effect for the information of small blood vessels.