Image denoising algorithm based on Demons algorithm

Abstract

The invention relates to an image denoising algorithm based on a Demons algorithm. The method comprises the following steps: firstly, on the basis of the Demons algorithm, regarding a diffusion process as image registration, and establishing a new Demons denoising algorithm based on image registration, wherein the PM algorithm, with relatively classical denoising performance, of the algorithm is preferable; secondly, in view of that local feature depending on gradient information representation images is insufficient in an image denoising process and second-order differential quantities contain richer information, taking a level set curvature as a driving force factor for controlling an image structure to be introduced in an image registration denoising algorithm, and establishing an image denoising algorithm of gradient and curvature dual driving force, namely a dual driving algorithm; finally, adopting an additive operator splitting algorithm (AOS algorithm) to process the algorithm to obtain an image after denoising. The denoising performance is superior, and the integral structure of the image is kept intact, the image SNR (Signal to Noise Ratio) after denoising is improved by about 15 dB compared with other Demons algorithms and is improved by about 25 dB compared with the PM algorithm, and the definition is also greatly promoted.

Description

technical field [0001] The invention relates to the field of image processing, and is an image denoising algorithm based on partial differential equations, which is improved based on the Demons algorithm. Background technique [0002] Digital images are the source of information in many disciplines, but images often introduce noise due to various reasons during the acquisition process. Therefore, in the field of image processing and computer, image denoising is one of the most fundamental problems. In recent decades, partial differential equation methods have been widely used in image processing, and significant progress has been made in image denoising, segmentation, edge detection, and enhancement. [0003] So far, researchers have proposed many anisotropic diffusion algorithms, the most classic of which is the second-order partial differential algorithm that makes the conductance dependent on the image gradient, namely the PM algorithm. With the continuous deepening of ...

AI Technical Summary

Problems solved by technology

Due to the low timeliness and high complexity of the traditional algorithm, and excessive smoothing and insufficient smoothing often occur in the processing process, this algorithm is improved on the basis of the Demons algorithm to simplify the image anisotropic denoising process into an image In the registration process, there is no need to consider the design of diffusion function, gradient threshold, and distinguishing edges, which reduces the complexity of the algorithm and improves the timeliness of the algorithm, thus simplifying the problem of image denoising, and efficiently using the overall structure function to control the image structure

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