Image scaling method capable of controlling main body size based on content

Abstract

The invention provides an imaging scaling method capable of controlling main body size based on content, belonging to the technical field of information. The method comprises six steps of calculating gradient, acquiring saliency, calculating importance degree, initializing grid, deforming the grid and mapping image content, wherein a multi-resolution saliency model based on sparsity characteristic provided in step 2 can more exactly identify the main body area with different sizes in the same image compared with the existing mainstream method; in step 3, the weighted average of gradient and saliency is taken as the importance degree, which can better identify edges and inner areas of the image main body; and in the step 5, gridding deformation energy can carry out optimal control in accordance with the importance degree so as to cause the grid with great importance degree to approximate unified scaling of assigned scaling factor as far as possible and gather the deformation resulting from image size and length and width proportion in isomorphism areas with small importance degree as far as possible, thereby protecting the main body areas in the image from deforming, and meeting demands of controlling the main body size by users in accordance with the content.

Description

Technical field: [0001] The invention relates to a content-based image scaling method with controllable subject size, which belongs to the field of information technology. Background technique: [0002] Content-based image scaling, that is, an image scaling technology that keeps the main body area of ​​the image unchanged when the image size and aspect ratio change. In recent years, with the rapid growth of display devices with various aspect ratios and resolutions, this technology has become one of the research hotspots in the field of digital image processing. Among them, automatic identification of content importance and scaling based on importance weight are its two main stages. In the process of content importance recognition, since there are often multiple subject areas of different sizes in the same image, multi-resolution scale images must be used for recognition. In terms of scaling, the grid-based arbitrary image scaling technology has become one of the effective...

AI Technical Summary

Problems solved by technology

However, the existing technology uses a uniform zoom grid with various scale factors that maintain the aspect ratio as an optimization mechanism to automatically reduce the size of the main body area in the resulting image as the image size itself shrinks, and enlarges and enlarges, which cannot meet the requirements of The user needs to control the size of the body according to the image content

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