Notes on Resizing Images

Notes on Resizing Images

July 2026

Given the influx of AI and readily available tools for things like super resolution (e.g. RealESRGAN), better ways to enhance images when resizing downwards becomes important as well.

The broad idea we should use looks like:

 1orig_w, orig_h = img.size
 2new_h = round(TARGET_WIDTH * orig_h / orig_w)
 3
 4# Gaussian blur pre-filter for anti-aliasing
 5blurred = img.filter(ImageFilter.GaussianBlur(radius=0.5))
 6
 7# One-step Lanczos downscale
 8resized = blurred.resize((TARGET_WIDTH, new_h), Image.LANCZOS)
 9
10output_path = OUTPUT_DIR / f"page_{page_num:03d}.png"
11resized.save(output_path, "PNG", optimize=True)

Where setting something like radius being related to the size of the image scaled. For example, if the resulting image is half the size log the original image, a radius=0.5 is probably appropriate. Whereas if it is 1/5 of the size maybe radius of 1 to 1.5 is better. If you’re after an equation, radius=math.log(scale) is pretty close to the target.