Compress · Convert · Resize — A Unified Practical Guide
Overview: Compression, conversion, and resizing are core operations across web development, media production, data engineering, and everyday tooling. Though they serve different purposes—reducing size, changing representation, and altering dimensions—they are often combined in practical workflows. This guide explains concepts, tools, examples, and best practices to handle these tasks reliably and at scale.
1. Concepts & relationships
Compress reduces data size by exploiting redundancy (lossless) or perceptual tolerance (lossy). Convert changes format or representation (e.g., PNG → JPEG, DOCX → PDF, JSON → CSV). Resize changes pixel dimensions or sampling resolution for images and video. In real workflows you often resize first, then compress and convert to the desired output format to balance quality, compatibility, and size.
2. When to use each operation
- Resize: When target display size or storage constraints require different pixel dimensions (thumbnails, responsive images, print sizes).
- Convert: For compatibility or feature reasons (e.g., convert to WebP for web, to PDF for sharing, to MP3 for audio playback).
- Compress: To reduce file size for transfer or storage—choose lossless for code/text and lossy for photos/media where reduced fidelity is acceptable.
3. File formats and trade-offs
Pick formats by the use case:
- Images: JPEG (photo, lossy), PNG (lossless, transparency), WebP/AVIF (modern, efficient), SVG (vector, scales infinitely).
- Video: MP4/H.264 (compatibility), WebM/VP9 or AV1 (efficiency).
- Audio: MP3/AAC (compatibility), Opus (efficiency).
- Documents: PDF for sharing/printing, DOCX for editing.
4. Resizing — quality & algorithms
Use appropriate interpolation depending on content:
- Nearest neighbor for pixel art.
- Bicubic/Lanczos for photographic content when downscaling.
- AI upscalers (ESRGAN) for upscaling when detail recovery matters.
# ImageMagick example: resize while keeping aspect ratio magick input.jpg -resize 1200x -quality 85 output-1200.jpg
5. Conversion — preserving intent
Conversion must preserve the information that matters. Converting HTML to PDF requires attention to CSS, page breaks, and fonts. Converting JSON to CSV requires schema/flattening decisions. Document conversions should consider metadata and accessibility (tags, alt text).
6. Compression — lossless vs lossy
Choose lossless for code and archives, lossy for photos and streaming media. For web text assets, Brotli or gzip are standards; for images use format-native compression (WebP/AVIF). For backups prefer zstd or xz depending on speed/ratio needs.
7. Tooling: combined workflows
Practical pipelines combine multiple tools. Example: upload → sanitize → resize → convert → compress → store/serve.
Example: Web image pipeline
- Upload: accept user image and validate type/size.
- Sanitize: strip dangerous metadata or scripts (SVG).