You Can Increase the Resolution of an Image, but Your Source File Decides How Far

Image upscaling increases pixel dimensions by predicting plausible new pixels rather than recovering detail absent from the original, so a 2x scale doubles each edge and produces four times as many pixels while a 4x scale produces sixteen times as many. The described options include a free, privacy-focused browser tool using Swin2SR locally through WebGPU, but it accepts only images with a maximum 384-pixel long edge and outputs up to 768 pixels; hosted tools using Real-ESRGAN or Tencent models, which support larger files, scales up to 4x or 10x, and in some cases exact target dimensions; and Adobe Super Resolution, which creates a new DNG at twice the width and height for compatible raw, JPEG, and TIFF files. Selecting a method should depend on the original image size, target dimensions, and source quality rather than the largest advertised multiplier, since large or already sharp files may gain little and browser processing can reduce larger inputs before enhancement. Best practices include using the original file, cropping tightly around the subject, applying one upscale pass rather than stacking multiple passes, and checking results at full size, while vector logos, source text documents, and severely blurred or degraded images are generally better handled through their originals because AI-generated detail can introduce artifacts, softened text, or artificial-looking surfaces.

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