Automatic hierarchical atlas collaging method based on image importance

Abstract

The present invention provides an automatic hierarchical atlas collaging method based on image importance. The method comprises four steps: step 1: segmenting an image by using a Meanshift algorithm, extracting a salient area in the image in a rectangle manner, and if there are a plurality of salient areas, merging the salient areas into one; step 2: calculating to obtain a different degree of an image foreground and background through color complexity and pixel gradient complexity of the image foreground and background, then calculating an average value of different degrees between the image and other images in an atlas, to obtain a representing degree of the image, and finally averaging the different degree of the foreground and background and the different degrees between images, to obtain importance of each image; step 3: storing a hierarchical relationship of the atlas by using an XML file, and using the above obtained importance of the image as a weight of a node and storing a rectangle outline circumscribing the salient area; and step 4: using a Voronoi tree to visualize a hierarchy of the atlas, representing a subset of the atlas or an importance weight of the image by using a canvas area, and automatically collaging the salient area of each image according to the rectangle outline of the salient area of the node and an image zooming technology.

Description

technical field [0001] The invention relates to an atlas processing technology, in particular to an automatic image collage method with excellent visual effects. Background technique [0002] With the improvement of the performance of smartphones and the upgrade of camera pixels, people are more and more used to recording the details of life by taking pictures casually. How to browse and manage more and more photos has become a problem that people pay attention to. Although various pictures, photo-sharing software and websites emerge in an endless stream, enabling people to share photos with others. However, a large number of images make it difficult to browse and retrieve, and the commonly used classification storage method also makes it possible to only see the folder name when viewing a certain type of image, but cannot obtain specific image information. The image collage technology aims to collage multiple images in one canvas, allowing users to get more image informat...

AI Technical Summary

Problems solved by technology

Some automatic image collage technology solutions have been proposed, but there are certain shortcomings, such as the number of supported images is small, generally 20 to 40, and too many images will lead to poor visual effects. And cannot support hierarchical atlas data

[0003] For example, Microsoft provides an image collage software AutoCollage, which can extract the ROI area in the image, but it is time-consuming, and the shape division of the canvas is relatively simple

In the literature, YuZongqiao proposed to use the circular layout method for image collage. It calculates the importance of the image separately, and then divides the canvas by circumscribed circles. The disadvantage is that the calculation method of image importance is not effective and the canvas utilization rate is low.

In the literature, LiuTie et al. proposed a collage method that distinguishes different important areas of the image, and then occludes non-important areas from each other. This method allows the canvas to mainly present the ROI area in the image. The disadvantage is that the view is more confusing, and the underlying image The probability of being blocked is high

Brian et al. proposed a layout scheme called BRIC (blocked recursive image composition), which takes less time but has a single collage effect

[0004] The image collage scheme mentioned above does not achieve a good balance between the collage effect and efficiency, and only considers a small number of image collages on the same layer, and does not support large-scale multi-level multi-theme atlases. Collage Visualization Scheme

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