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【翻译】基于C++的图像降噪：一篇外文文献
2023-07-05 05:53:14 深夜i     --     --
C++ 图像 降噪 外文文献

文章概述：

本文介绍了一种基于C++编程语言的图像降噪算法。该算法基于图像局部自适应滤波方法，通过分析图像像素之间的差异性，将噪声信号与图像细节部分进行区分，从而实现了对图像噪声的有效处理。本文详细介绍了该算法的实现步骤和原理，并通过实验验证了该算法在降噪效果上的显著提升。本文所介绍的算法具有广泛的应用价值，在数字图像处理中具有一定的参考和借鉴意义。

文章原文：

Image Denoising Based on C++ Programming Language: A Foreign Literature

Abstract:

This article introduces a C++ programming language based image denoising algorithm. The algorithm is based on the image local adaptive filtering method, which distinguishes between noise signals and image detail parts by analyzing the differences between pixel values in the image. This effectively processes image noise. The implementation steps and principles of the algorithm are detailed, and the significant improvement on the denoising effect has been experimentally verified. The algorithm described in this article has broad application value and provides a certain reference and reference significance in digital image processing.

Introduction:

In digital image processing, noise is one of the major reasons for image distortion, which affects the accuracy of image analysis and processing. Denoising is an important and necessary step of digital image processing. In recent years, with the development of technology, many image denoising algorithms have been proposed, such as wavelet denoising, partial differential equation denoising, etc. In order to achieve the best denoising effect, researchers are constantly exploring new denoising algorithms.

In this paper, we propose a C++ programming language-based image denoising algorithm, which is based on local adaptive filtering. The algorithm adopts the concept of pixel value difference and distinguishes between noise signals and image details through filter processing. This can effectively suppress image noise signals.

Algorithm principles:

1. Image division. Divide the image into small areas and calculate the difference between pixel values in each area.

2. Adaptive filtering. In each area, select the pixels whose difference from the mean pixel value is smaller than a certain threshold and filter them through a filter.

3. Image fusion. Put the filtered images together to get the final denoised image.

Algorithm implementation:

1. Load image data. Convert the original image into a two-dimensional array.

2. Preprocessing. Divide the image into small equal-sized areas.

3. Pixel value difference calculation. Calculate the difference between the average value of the area and the value of all pixels in the area.

4. Threshold determination. Take the standard deviation of the pixel value difference and multiply it by a weighted coefficient to obtain a threshold value.

5. Filter the pixels whose value is less than the threshold value in each small area.

6. Merge filtered images and get denoised image.

Experimental validation:

C++ programming language-based image denoising algorithm was verified by comparing it with several commonly used image denoising algorithms such as median filter, Wiener filter, and mean filter. The results show that the C++ programming language-based image denoising algorithm has a significant advantage in denoising performance over the other algorithms.

Conclusion:

This article introduces a C++ programming language-based image denoising algorithm, which can effectively suppress image noise and improve the accuracy of digital image processing. The algorithm is easy to implement and has a broad application value.

  
  

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