<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>反卷积 on Mi&amp;Bee Blog</title><link>/tags/%E5%8F%8D%E5%8D%B7%E7%A7%AF/</link><description>Recent content in 反卷积 on Mi&amp;Bee Blog</description><generator>Hugo -- gohugo.io</generator><language>zh-CN</language><managingEditor>蓝宝石的傻话</managingEditor><lastBuildDate>Tue, 16 Jun 2026 10:00:00 +0800</lastBuildDate><atom:link href="/tags/%E5%8F%8D%E5%8D%B7%E7%A7%AF/rss.xml" rel="self" type="application/rss+xml"/><item><title>空间域恢复与边缘保持滤波</title><link>/posts/physical-world/spatial-domain-restoration/</link><pubDate>Tue, 16 Jun 2026 10:00:00 +0800</pubDate><guid>/posts/physical-world/spatial-domain-restoration/</guid><description>&lt;p&gt;上一篇介绍了频率域的图像处理方法——通过傅里叶变换将图像转换到频域，然后进行滤波、复原等操作。但频率域方法有时不太直观，尤其是我们更习惯直接操作像素。&lt;/p&gt;</description></item></channel></rss>