Image noise is the random variation of brightness or color information in the images. Noise can enter the picture during capturing or transmitting. Different linear and nonlinear methods have been implemented to remove the noise from an image, but transformation of wavelets is becoming increasingly important. We propose a fundamental concept for disintegrating the input bubble, sound, and movement signal of the object/camera into appropriate coefficients by transforming the empirical wavelet and making full changes. A new messy screen search strategy is used to assess the variability at each pixel of the decomposed picture. Empirical wavelet is a kind of wavelet tailored to the data being handled. This is an adaptive technique for decomposing the signal or picture to a set of sections recognized as phases. This wavelet transform is relevant for de‐noising, decompression, etc. Chaotic squirrel search optimizers imitate the vibrant feeding behavior and efficiency of northern flying squirrels, called gliding. Gliding is a powerful system used for lengthy ranges by tiny mammals. Compared to other wavelet transformations, the median peak signal for noise ratio (PSNR) enhancement obtained by EWT is 73%. Numerical tests indicate that our proposed method could be able to substantially enhance restored pictures' efficiency and achieve greater SNR and structural similarity index scores likened to the present state of the art methodologies.

中文翻译：

---

结合经验小波变换和总变化的混沌松鼠搜索优化方法

图像噪声是图像中亮度或颜色信息的随机变化。在捕获或传输过程中，噪声会进入图像。已经实现了不同的线性和非线性方法来去除图像中的噪声，但是小波的变换变得越来越重要。我们提出了一个基本概念，通过变换经验小波并进行完全更改，将输入气泡，声音和物体/相机的运动信号分解为适当的系数。一种新的混乱屏幕搜索策略用于评估分解图片的每个像素处的可变性。经验小波是针对要处理的数据量身定制的一种小波。这是一种自适应技术，用于将信号或图片分解为一组被识别为相位的部分。这种小波变换与降噪，减压等有关。混沌的松鼠搜索优化器模仿了北方飞鼠的活跃进食行为和效率，称为滑翔。滑翔是一个功能强大的系统，可用于小型哺乳动物的长距离飞行。与其他小波变换相比，通过EWT获得的中值峰值信噪比（PSNR）增强为73％。数值测试表明，我们提出的方法能够显着提高恢复的图片的效率，并获得与现有技术方法类似的更高的SNR和结构相似性指数。滑翔是一个功能强大的系统，可用于小型哺乳动物的长距离飞行。与其他小波变换相比，通过EWT获得的中值峰值信噪比（PSNR）增强为73％。数值测试表明，我们提出的方法能够显着提高恢复的图片的效率，并获得与现有技术方法类似的更高的SNR和结构相似性指数。滑翔是一个功能强大的系统，可用于小型哺乳动物的长距离飞行。与其他小波变换相比，通过EWT获得的中值峰值信噪比（PSNR）增强为73％。数值测试表明，我们提出的方法能够显着提高恢复的图片的效率，并获得与现有技术方法类似的更高的SNR和结构相似性指数。