<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Image Processing | My CV</title><link>https://tipiorgup.github.io/tags/image-processing/</link><atom:link href="https://tipiorgup.github.io/tags/image-processing/index.xml" rel="self" type="application/rss+xml"/><description>Image Processing</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Thu, 08 Oct 2026 00:00:00 +0000</lastBuildDate><image><url>https://tipiorgup.github.io/media/icon_hu7729264130191091259.png</url><title>Image Processing</title><link>https://tipiorgup.github.io/tags/image-processing/</link></image><item><title>SXM Image Analyzer</title><link>https://tipiorgup.github.io/project/sxm-analyzer/</link><pubDate>Thu, 08 Oct 2026 00:00:00 +0000</pubDate><guid>https://tipiorgup.github.io/project/sxm-analyzer/</guid><description>&lt;h2 id="description">Description&lt;/h2>
&lt;p>&lt;strong>SXM Image Analyzer&lt;/strong> is a &lt;a href="https://streamlit.io/" target="_blank" rel="noopener">Streamlit&lt;/a> app for quickly viewing and cleaning up scanning probe microscopy (SPM/STM) images saved in the Nanonis &lt;code>.sxm&lt;/code> format, with no local installation needed. Upload a &lt;code>.sxm&lt;/code> file (up to 200 MB) to see the image and its acquisition metadata right away.&lt;/p>
&lt;p>Open the app directly via the &lt;a href="https://sxmfkf.streamlit.app/" target="_blank" rel="noopener">site link&lt;/a>.&lt;/p>
&lt;h2 id="features">Features&lt;/h2>
&lt;h3 id="original-image">Original image&lt;/h3>
&lt;ul>
&lt;li>View the raw topography image as recorded.&lt;/li>
&lt;li>Download the unfiltered image (PNG), the scan metadata (TXT) and the STM data grid (NPZ) for further analysis in Python.&lt;/li>
&lt;/ul>
&lt;h3 id="processing">Processing&lt;/h3>
&lt;p>Use the &lt;strong>Process&lt;/strong> tab to enhance the image interactively:&lt;/p>
&lt;ul>
&lt;li>&lt;strong>FFT filtering&lt;/strong> with Gaussian, Blackman–Harris or exponential windows and an adjustable width (σ), to remove high-frequency noise.&lt;/li>
&lt;li>&lt;strong>Unsharp masking&lt;/strong> with adjustable radius and amount, to sharpen molecular and atomic features.&lt;/li>
&lt;li>&lt;strong>Image transforms&lt;/strong>: contrast inversion and cosine transform.&lt;/li>
&lt;/ul>
&lt;p>The processed image, processed raw image and metadata can be downloaded.&lt;/p>
&lt;h3 id="analysis-coming-soon">Analysis (coming soon)&lt;/h3>
&lt;p>Dedicated analysis modes for specific adsorbates are under development: &lt;strong>chitosan&lt;/strong>, &lt;strong>RNA&lt;/strong>, &lt;strong>proteins&lt;/strong>, &lt;strong>chlorophyll&lt;/strong> and &lt;strong>glycolipids&lt;/strong>.&lt;/p>
&lt;h2 id="tutorial">Tutorial&lt;/h2>
&lt;p>A step-by-step notebook showing how to load &lt;code>.sxm&lt;/code> files and apply these filters in Python is available on &lt;a href="https://github.com/tipiorgup/SXM-filters" target="_blank" rel="noopener">GitHub&lt;/a>.&lt;/p>
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