How PNG Compression Works: The Technical Explanation Made Simple

By admin · Jun 22, 2026

Ever wondered what actually happens when you click "compress" on a PNG file? Behind the scenes, some clever mathematics and algorithms are working to shrink your file while keeping it looking great.

Step 1: Understanding How PNG Stores Image Data

A PNG file is essentially a grid of pixels. Each pixel has a color value. For a standard 24-bit PNG, each pixel stores:

• Red value (0–255)
• Green value (0–255)
• Blue value (0–255)

For PNG images with transparency, there's also an Alpha value (0–255). A 1000×1000 pixel image has 1,000,000 pixels — at 4 bytes per pixel, that's 4 MB of raw data before any compression.

Step 2: PNG Filtering

Before PNG applies compression, it runs the image through filtering. This transforms the data into a format that compresses more efficiently. PNG uses five filter types: None, Sub, Up, Average, and Paeth.

The key insight: differences between neighboring pixels are usually small. And small numbers compress much better than random large numbers.

Step 3: DEFLATE Compression

After filtering, PNG applies the DEFLATE algorithm to compress the filtered data. DEFLATE combines two techniques:

LZ77 (Pattern Matching)

LZ77 looks for repeating sequences in the data and replaces them with references. Instead of storing the same pattern 10 times, it stores it once and says "repeat this 9 more times."

Huffman Coding

Huffman coding assigns shorter codes to more frequent values. Common pixel values get short codes, rare values get longer codes — resulting in an overall smaller file.

Together, these techniques reduce PNG data significantly — but this is all still lossless at this stage. No visual data has been removed.

Step 4: Color Quantization (Lossy Part)

Color quantization reduces the number of unique colors in an image. The algorithm:

1. Analyzes all colors in the image
2. Groups similar colors into clusters
3. Replaces each cluster with a single representative color
4. Converts the image from 24-bit/32-bit to 8-bit (256 colors max)

This converts the image from a Truecolor PNG (PNG-24/32) to an Indexed PNG (PNG-8). The result: dramatically smaller file size, with visual quality so close to the original that most people cannot tell the difference.

The Technology Behind compresspngfile.com: pngquant

compresspngfile.com uses pngquant, the industry-leading lossy PNG compression library. Here's what pngquant does:

• Uses a modified Median Cut algorithm for color quantization
• Applies Floyd-Steinberg dithering to minimize visible color banding
• Preserves full alpha channel transparency
• Outputs a fully standards-compliant PNG-8 file

The result is files that are 60–80% smaller than the original, while maintaining excellent visual quality.

Metadata Removal

PNG files often contain metadata — creation date, software used, camera settings, color profiles, thumbnail previews. This metadata adds no visual value but takes up file space. PNG compression tools strip this metadata, saving additional kilobytes.

Why Some Images Compress Better Than Others

Conclusion

PNG compression is a combination of smart mathematics: filtering to prepare data, DEFLATE to compress it losslessly, and color quantization to achieve dramatic size reductions with minimal visual impact. You don't need to understand all the math to benefit from it — that's what compresspngfile.com is for.