Research On The Improved Adaptive Weighted Median Denoising Algorithm

With the continuous development of science and technology,the application scope of digital image technology is increasingly widening.In the process of acquisition and transmission,digital image is susceptible to the interference of external or internal factors,such as imaging sensor being sensitive to the influence of imaging environment conditions and their quality,image signals being vulnerable to the influence of light and atmosphere factors in the wireless transmission,which results in image degradation and affects the subsequent image process.In order to improve the quality of corrupted image,the research of the image filtering algorithm is proposed in the paper.Firstly,the basic theory of digital image and the causes of image noise,the mathematical model of the noise are introduced in brief,and the basic principles of the mean filtering algorithm and the median filtering algorithm are studied in the paper.Secondly,this paper analyses seven kinds of the improved median filtering algorithm and analyzes their advantages and disadvantages.According to the above algorithm,which is difficult to meet the application requirements in the removal of noise and image feature retention,an improved adaptive weighted median denoising algorithm is proposed.image vague is due to the traditional filtering algorithm neglects to process the image boundary pixel points,the size of the image is expanded by replicating the most lateral boundary pixel points,which can make all the pixel points on the image filtered by filtering template.In order to solve the problem of the misjudgment of the noise detection,the algorithm designs a noise detection function based on the correlation of pixel points,which is used to determine whether the suspected noise is real noise or not,which realizes a more accurate detection of noise points.For the pixel corrupted by noise,the algorithm makes the pixel gray value of the window in the neighborhood multiply by its normalized and weighted coefficient,and then accumulates the sum of all the pixels,which replaces the median value as the filtered output.The method not only can effectively suppress the interference of the neighborhood and noisy pixel points,but also maximizes the protection of image feature.The simulation results show that the proposed algorithm can reduce noise and preserve image feature very well.The obtained peak signal noise ratio parameters are higher than the existing filtering algorithm.meanwhile,the proposed algorithm has a lower mean absolute error parameters.Finally,the image technology has been deeply applied in the image preprocessing field,the image quality requirements of which are getting higher and higher.In this paper,the algorithm has a good advantage of removing noise and retaining image feature,and can effectively improve the quality of the image,which is helpful to improve the image preprocessing effect.