The Science Behind Image Compression: Algorithms Explained
Published by ImageCompressor | Updated 2025
Introduction
Behind every compressed image lies a series of powerful algorithms working to balance quality and file size. Understanding these techniques helps developers and image professionals make better optimization choices. In this article, we explore the science behind the most common image compression methods.
Lossy vs. Lossless Algorithms
- Lossy compression: Removes data to reduce size (JPEG, WebP, AVIF)
- Lossless compression: Retains all original data (PNG, GIF, SVG)
Core Algorithms Used in Compression
1. Discrete Cosine Transform (DCT)
Used in JPEG and WebP, DCT converts image blocks into frequency data. High-frequency details (fine textures) are discarded or compressed more heavily than low-frequency areas (smooth regions).
2. Quantization
This step rounds off DCT values based on a quality matrix. It controls how much detail is lost and contributes most to file size savings in lossy compression.
3. Huffman Coding
An entropy encoding method that replaces common values with short binary codes and rare values with longer ones. Improves overall compression ratio without further quality loss.
4. Run-Length Encoding (RLE)
Used in lossless formats like GIF. Stores repeating pixel values efficiently (e.g., 10 black pixels becomes “10B”).
5. Deflate Compression
Used in PNG. Combines LZ77 and Huffman encoding. Efficient for graphics with limited color palettes.
How JPEG Uses These Steps
- Convert to YCbCr color space
- Split image into 8x8 pixel blocks
- Apply DCT to each block
- Quantize the result
- Encode with Huffman coding
AVIF and WebP Enhancements
Both formats use more advanced transformation methods like ANS and better entropy models to achieve higher compression at similar or better visual quality than JPEG.
Developer Tips
- Use WebP or AVIF for photos on modern browsers
- Use PNG only when lossless transparency is required
- Understand trade-offs between speed and quality during encoding
Conclusion
Whether you're optimizing for web speed, bandwidth, or visual clarity, understanding how image compression works lets you make smarter choices. Tools like ImageCompressor make it easy to apply these principles without writing code — but now you know what's happening behind the scenes.