Image smoothing method and image smoothing device

Abstract

An embodiment of the invention provides an image smoothing method which comprises the steps of firstly performing smoothing processing on an original image by means of bilaterial filtering and transformation domain filtering in a local smoothing method, thereby obtaining a guiding image; constructing a least square model for the original image, the guiding image and a preset smooth image by means of a least square method, adding a constraint function to the preset smooth image for controlling sparsity of the smooth image, and obtaining a smooth energy objective function; and finally solving the function by means of a semi-secondary splitting method and an alternative fixed-variable method, thereby obtaining the smooth image which is obtained through performing smoothing processing on the original image. The image smoothing method has advantages of realizing comprehensive consideration for global characteristics and local characteristics, improving structure component protection in the original image, restoring some details with high contrast, obtaining a good image smoothing effect and improving image identification accuracy. Furthermore the embodiment of the invention provides a corresponding image smoothing device for realizing the method. Furthermore high practicability of the method is realized, wherein the image smoothing device has corresponding advantages.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of image processing, and in particular, to an image smoothing method and device. Background technique [0002] With the rapid development of computer image processing technology, image smoothing technology has also developed rapidly in order to meet the high requirements of the current image processing technology field. Image smoothing technology refers to the image processing technology used to highlight the wide area, low-frequency components, and main parts of the image or suppress image noise and interference high-frequency components, make the image brightness gradually change, reduce the abrupt gradient, and improve image quality. It is widely used In image segmentation, denoising, detail enhancement, object classification, edge extraction and other fields. [0003] In the process of image acquisition and transmission, it is unavoidable to be disturbed by noise and unimportan...

AI Technical Summary

Problems solved by technology

The structure of the global smoothing method keeps the optimization framework of the constraint items more flexible, and it is better than the local smoothing method for the global features of the image, especially for the unimportant details such as the background part of the image, but the global smoothing algorithm often affects the local high contrast noise. poor smoothing

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