Image Resizer

Image resizing changes the pixel dimensions of an image. When you resize an image to smaller dimensions, pixels are removed or merged — a process called downsampling. When you increase dimensions, new pixels are interpolated between existing ones — upsampling. The quality of the resize depends on the interpolation algorithm used: bilinear interpolation (fast, smooth results), bicubic (sharper, higher quality, slower), and Lanczos (highest quality for significant size reductions). For web use, resizing images to their display dimensions is one of the most impactful performance optimizations available. A 4000×3000px photo served in a 800×600px container wastes 25x the bandwidth. The AllTools Image Resizer uses the browser's Canvas API to resize images locally, applying high-quality interpolation without sending your images to any server. You can resize by exact pixel dimensions, by percentage of original size, or by constraining to a maximum dimension while maintaining aspect ratio.

Resizing and compression are complementary but distinct optimizations, and knowing when to use each is key to achieving the best results. Resize when your image dimensions are larger than the display context — for example, uploading a 6000×4000px photo to a website that shows it at 1200×800px. Resizing reduces file size by eliminating pixels that will never be displayed. Compress when the image dimensions are already appropriate but the file size is still too large — for example, a 1200×800px image that is 800KB when it should be 80KB. Compression reduces file size by discarding redundant color and pattern data. For the best results, resize first to the correct dimensions, then compress at the appropriate quality level. This two-step approach consistently produces smaller files than applying only one technique. The AllTools suite handles both steps: resize here, then use the Image Compressor for quality optimization.