<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Saliency on RawCull</title><link>https://techrawcull.netlify.app/tags/saliency/</link><description>Recent content in Saliency on RawCull</description><generator>Hugo</generator><language>en</language><lastBuildDate>Thu, 30 Jul 2026 07:59:27 +0200</lastBuildDate><atom:link href="https://techrawcull.netlify.app/tags/saliency/index.xml" rel="self" type="application/rss+xml"/><item><title>Detailed Sharpness Scoring</title><link>https://techrawcull.netlify.app/docs/detailsharpnessscoring/</link><pubDate>Wed, 15 Jul 2026 00:00:00 +0000</pubDate><guid>https://techrawcull.netlify.app/docs/detailsharpnessscoring/</guid><description>&lt;h1 id="detailed-sharpness-scoring"&gt;Detailed Sharpness Scoring&lt;a class="td-heading-self-link" href="#detailed-sharpness-scoring" aria-label="Heading self-link"&gt;&lt;/a&gt;&lt;/h1&gt;
&lt;p&gt;This page explains, step by step, where RawCull computes sharpness scores, what code is involved, what the score means, and which factors can move the result up or down.&lt;/p&gt;
&lt;p&gt;The short version: RawCull does not ask &amp;ldquo;is the whole image contrasty?&amp;rdquo;. It asks &amp;ldquo;how much reliable edge detail exists in the useful part of the image, especially around the subject or the camera AF point?&amp;rdquo;. The score is then used for sharpness sorting, burst ranking, saved scoring results, and inspection badges.&lt;/p&gt;</description></item><item><title>Detailed Focus Mask Computation</title><link>https://techrawcull.netlify.app/docs/detailsfocusmask/</link><pubDate>Mon, 29 Jun 2026 00:00:00 +0000</pubDate><guid>https://techrawcull.netlify.app/docs/detailsfocusmask/</guid><description>&lt;h1 id="detailed-focus-mask-computation"&gt;Detailed Focus Mask Computation&lt;a class="td-heading-self-link" href="#detailed-focus-mask-computation" aria-label="Heading self-link"&gt;&lt;/a&gt;&lt;/h1&gt;
&lt;p&gt;This page explains, step by step, how RawCull computes the visible focus mask: where the work starts in the UI, which model and engine methods run, how the bitmap overlay is produced, what the intermediate values mean, and which factors can change the final result.&lt;/p&gt;
&lt;p&gt;The short version: the focus mask is not a camera focus-point display. It is a computed overlay built from local edge energy. RawCull first finds useful regions to inspect, then computes a Laplacian edge-energy image, ranks local patches, thresholds the strongest evidence, colorizes it, clips it to the selected patch areas, and finally draws the result over the photo.&lt;/p&gt;</description></item></channel></rss>