A Hybrid Bilateral Image Filtering Method

Abstract

The invention provides a hybrid bilateral image filtering method. The technical solution is: use the Laplacian edge detection operator to calculate the Laplacian output value of each pixel in the image to be filtered; use the bimodal method or a specified threshold to detect all Laplacian output values, and obtain Initial edge point pixels; perform morphological expansion on the initial edge point pixels to obtain final edge point pixels and non-edge point pixels; perform bilateral filtering on edge point pixels, and perform Gaussian filtering on non-edge point pixels to obtain the final filtering result. The beneficial effect of the present invention is that the speed of bilateral filtering can be effectively improved without reducing the filtering effect.

Description

technical field [0001] The invention belongs to the technical field of image enhancement, and relates to a mixed bilateral image filtering method combining bilateral filtering and Gaussian filtering, which improves the filtering speed without affecting the filtering effect. Background technique [0002] Filtering is one of the important contents of image processing and computer vision. Its basic principle is to perform neighborhood operations on the brightness values ​​of each pixel in the image and the pixels in its neighborhood, that is, to perform local weighted average convolution operations. The classic Gaussian filter comes from this idea, but it also blurs the edges of the image while smoothing the image. [0003] Bilateral filtering is a filtering method that can effectively smooth the image while maintaining the edge of the image. It has the characteristics of non-iterative, local and simple. Like the classic Gaussian filter, the bilateral filter only uses the idea...

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Problems solved by technology

This characteristic of bilateral filtering also makes the calculation consumption very large

[0004] In addition, bilateral filtering does not consider prior information such as image content, but performs complex bilateral filtering calculations on all pixels of the image

Since the bilateral filtering will be weakened into Gaussian filtering in a uniform area with small grayscale changes, this will cause a great waste of calculation; an extreme case is to process a pure color image, the bilateral filtering and Gaussian filtering obtained is the same result, but the computational complexity of bilateral filtering is greatly increased

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