Hotspot map generation method based parallel acceleration

Abstract

The invention relates to a hotspot map generation method based on parallel acceleration, and adopts parallel technology to perform correlation calculation of hotspot map generation. The method includes the following steps: 1) according to influence radii of a hotspots input by a user, calculating an influence factor distance matrix of the hotspots; 2) calculating superposed grey-scale map information of all hotspot influence ranges to generate a grey-scale map of a hotspot map; 3) according to color map information after calculation and mapping of the grey-scale map, generating a color map of the hotspot map; and 4) outputting and showing the colored hotspot map to the user. The hotspot map generation method based on parallel acceleration uses the GPU parallel technology to improve a conventional Heatmap algorithm for the first time, makes full use of a hardware acceleration ability, and ingeniously combines Arcgis, Opengl and WPF drawing technology, thus to effectively improve hotspot map generation efficiency, has relatively good practicability, intelligence and flexibility, and can be applied to the fields of GISs, virtual reality, image processing, industry visualization and the like.

Description

technical field [0001] The invention belongs to the field of image processing technology and heat map generation technology, and in particular relates to a heat map generation method based on parallel acceleration. Background technique [0002] Heat map, also called Heatmap, aggregates a large amount of data and uses a gradual color band to display it elegantly. The final effect is often better than the direct display of discrete points, and it can intuitively show the density or frequency of spatial data. . Heat maps have been used in many fields. For example, record the user's mouse click position in the Web page, display various spatial discrete point data, and so on. [0003] The heat map generation algorithm mainly includes the following four steps: [0004] 1) Set a radius for discrete points and create a buffer; [0005] 2) For the buffer of each discrete point, use progressive grayscale bands (complete grayscale bands are 0-255) to fill from inside to outside, fr...

AI Technical Summary

Problems solved by technology

Since these algorithms are all implemented in the CPU, the algorithm efficiency is low and the delay is serious when the input point data volume is large, the radius is large, and the screen resolution is large.

[0018] 2) The heat map analysis results are not suitable for practical application

These operations all involve traversal loop operations. If the operations are completed in the CPU, the time complexity is O(n) and O( w*h), seriously affecting performance

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