An image-guided filtering method and computing device

Abstract

The invention discloses a method for generating a guided image in guided filtering and a method for performing guided filtering processing on an image to be processed according to the guided image. The image guided filtering method comprises the steps that the method for generating the guided image is performed on the image to be processed so as to generate a gradient enhanced image and a second guided image; the maximum value and the minimum value of the pixel value in the second guided image are calculated; segmented processing is performed on the second guided image, and the standard deviation value of the pixel points in each segment is calculated; offset processing is performed on the second guided image so as to obtain the second guided image after offset processing; the adjusting coefficient of guided filtering is generated according to the gradient enhanced image; and guided filtering is performed on a certain channel image in the image to be processed according to the second guided image after offset processing and the adjusting coefficient so as to generate the image without noise point. The invention also discloses computing equipment for performing the method.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an image-guided filtering method and computing equipment. Background technique [0002] In the field of image processing technology, due to the influence of shooting environment, camera, etc., the captured image often contains noise, which affects the image quality. Therefore, it is often necessary to filter the image to remove the noise in the image. However, in the process of processing, filtering often leads to excessive blurring, which causes the loss of image edge details. For example, if there are scattered hairs in the skin of a portrait, if the filtering method is not selected properly, the effect of skin and hair adhesion will be caused, and the original image will be lost. detail features. [0003] Commonly used filtering methods such as Wiener filtering, Gaussian filtering, etc., will cause excessive blurring in image noise reduction processing, especially th...

AI Technical Summary

Problems solved by technology

However, in the process of processing, filtering often leads to excessive blurring, which causes the loss of image edge details. For example, if there are scattered hairs in the skin of a portrait, if the filtering method is not selected properly, the effect of skin and hair adhesion will be caused, and the original image will be lost. the details of the features

[0003] Commonly used filtering methods such as Wiener filtering, Gaussian filtering, etc., in image noise reduction processing, will lead to excessive blurring, especially the loss of image edge details

The guided filtering method has been widely used in image filtering processing because of its edge preservation and high calculation efficiency, but the guided filtering still has the following problems in the filtering process: (1) using fixed filter coefficients, for high-frequency images in color images Noise, guided filtering must be filtered cleanly, and reasonable filter coefficients need to be artificially selected to filter out high-frequency noise, but it will cause excessive blurring of the edge area of ​​​​the image, and the effect of edge preservation cannot be achieved; (2) guided filtering depends on the guided image Reasonable construction, if the guide map cannot maintain edge consistency with the original image, it will also cause abrupt or overly blurred areas in the filtered result map, and lose the edge preservation effect; (3) Noise and edges belong to areas with large gradients , if the noise and the edge area are treated equally, the edge-preserving effect will also be lost. When the guided filter is applied, it needs to use the differential information to construct a guided map for edge-preserving filtering, and the differential information is easily affected by noise points, which needs to be effectively processed.

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