Welcome back to Hidden Light Photography! If your stars sometimes look square, or your details look soft and mushy even when everything else is perfect — focus, tracking, exposure — then this video is your missing puzzle piece. Today we’re taking the next step in our image-quality series and breaking down Oversampling vs Undersampling — what they are, why they happen, and how to make sure your camera and telescope are perfectly matched to your sky conditions. 🌌 What you’ll learn in this video: • What oversampling really is (and why it makes your images soft) • Why undersampling causes blocky stars and jagged nebula edges • How your pixel scale interacts with atmospheric seeing • How to check if your setup is oversampled or undersampled • How bad seeing can make “high resolution” cameras perform worse • How to use the Astronomy Tools CCD Suitability Calculator • Why there’s a “Goldilocks zone” for pixel size and focal length • How to choose the right camera for your telescope • How to avoid wasting nights fighting physics instead of capturing detail ✨ In this video, I also demonstrate sampling using: • Pixel grids • Dots as photons • Realistic atmospheric motion • Side-by-side visual comparisons of undersampling, oversampling, and perfect sampling By the end, you’ll understand exactly why your images might look too soft or too blocky — and what you can do to fix it. 🧭 Search my entire video library by keyword (like “sampling”, “resolution”, “guiding”, “mosaic”): 👉 🛒 Want to upgrade your rig or support the channel? 👉 🔧 My 2025 Recommended Equipment List: 👉 💬 Not sure if YOU are over or under sampling? Drop your pixel size, telescope focal length, and seeing conditions in the comments — I respond to every question. 📧 Contact: Tony@ 🔔 Subscribe & join the mission: 👉 #Astrophotography #Oversampling #Undersampling #PixelScale #Sampling #HiddenLightPhotography #TelescopeCamera #AstronomyTools #ResolutionSeries #CCDCalculator #SeeingConditions #AstroImaging