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How Image Upscaling Works
Image upscaling increases the number of pixels in an image, making it larger while attempting to maintain visual quality. This tool uses high-quality interpolation algorithms running entirely in your browser via the Canvas API. When an image is enlarged, new pixels must be created between existing ones โ the algorithm determines how these new pixels are colored based on surrounding pixel values.
Upscaling Methods
- Bicubic โ uses 16 surrounding pixels to calculate each new pixel, producing smooth, natural-looking results. Best for photos.
- Bilinear โ uses 4 surrounding pixels, faster but slightly less sharp than bicubic. Good for web images.
- Bicubic + Sharpen โ bicubic upscaling followed by an unsharp mask to recover edge definition. Best overall quality for photos.
- Pixel Art (Nearest Neighbor) โ preserves hard pixel edges without blurring. Essential for pixel art and screenshots.
Limitations
Browser-based upscaling uses interpolation, not AI reconstruction. It cannot add detail that wasn't in the original image. For dramatically low-resolution images, consider AI upscaling tools like Gigapixel or Topaz Labs for the best results. This tool is ideal for moderate upscaling (2xโ4x) of reasonably-sharp source images.