图像复原：使用不同空间滤波技术的图像去噪比较分析
Image Restoration: A Comparative Analysis of Image De noising Using Different Spatial Filtering Techniques
AI总结：
本文比较了不同空间域滤波技术在图像去噪中的效果，通过引入噪声后应用多种滤波器，并使用PSNR和RMSE评估，发现不同滤波器对不同噪声模型的有效性存在差异。
摘要：
用于医疗和其他目的的采集图像可能会受到来自采集设备或环境的噪声影响。这可能会对图像中的信息产生不利影响。因此，需要通过去除噪声将图像恢复到原始状态。为了有效去除此类噪声，有必要预先了解存在的噪声模型类型。本工作通过首先向图像引入噪声，然后对图像应用不同的空间域滤波技术以去除噪声，来探索不同的去噪滤波器。采用不同的评估技术，如峰值信噪比（PSNR）和均方根误差（RMSE），来确定每种滤波器在给定图像噪声上的有效性。结果表明，某些滤波器在某些噪声模型上比其他滤波器更有效。
英文摘要：
Acquired images for medical and other purposes can be affected by noise from both the equipment used in the capturing or the environment. This can have adverse effect on the information therein. Thus, the need to restore the image to its original state by removing the noise. To effectively remove such noise, pre knowledge of the type of noise model present is necessary. This work explores different noise removal filters by first introducing noise to an image and then applying different spatial domain filtering techniques to the image to get rid of the noise. Different evaluation techniques such as Peak to Signal Noise Ratio(PSNR) and Root Mean Square Error(RMSE) were adopted to determine how effective each filter is on a given image noise. Result showed that some filters are more effective on some noise models than others.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
