Bokeh method based on salient region detection model

A technology of region detection and background blur, applied in biological neural network model, image data processing, image enhancement and other directions, can solve problems such as unclear boundaries, and achieve the effect of clear salient boundaries
CN108230243AInactive Publication Date: 2018-06-29FUZHOU UNIV
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
FUZHOU UNIV
Publication Date
2018-06-29
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention discloses a bokeh method based on a salient region detection model. The method comprises the following steps: obtaining an original image, constructing a salient region detection model on the basis of a convolutional network to obtain a salient image of the original image, training the obtained salient image in a fully connected conditional random field to obtain an optimized salientimage, performing binaryzation or segmentation processing on the optimized salient image to obtain a 01 matrix, and obtaining a foreground index matrix and a background index matrix; realizing globalblurring of the original image with a distance weighted average algorithm; finally, splicing an original foreground image with the blurred background image to obtain the blurred background image. With adoption of the method, not only can a complete salient region be detected accurately, but also the salient boundary is relatively clear, so that features of the foreground image can be kept duringbokeh, and content of the foreground image is not damaged.
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Description

Technical field

[0001] The invention relates to the technical field of digital image processing, in particular to a method for background blurring based on a salient region detection model. Background technique

[0002] Image background blur is a very common processing process in tasks such as image rendering, beautification, and enhancement. It can effectively highlight target objects and dilute the background information, thereby enhancing the visual effect. At present, some image processing software performs this processing well, but its processing methods all require manual annotation of the foreground area, which requires a lot of manpower and is not convenient for mass processing; in addition, the existing technology's fuzzy diffusion methods are all It is a regular shape and it is difficult to adapt to complex and changeable image content. The existing automatic background blur technology is immature in the foreground edge extraction, resulting in unclear boundaries, cutt...

Claims

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