How Image Compression Works: Lossy vs Lossless Explained

Every time you share a photo online, upload a document scan, or attach an image to an email, file size matters. A 5 MB photo that looks great on your phone can slow down a webpage, get rejected by a government portal, or eat up email attachment limits. That is where image compression comes in.

But not all compression is the same. Some methods throw away data to get smaller files. Others shrink files without losing a single pixel of information. Understanding the difference helps you make smarter choices about how you handle your images.

What is Image Compression?

At its core, image compression is about storing the same visual information using fewer bytes. Digital images are made up of pixels, and each pixel has color values that take up space. A raw, uncompressed image stores every single pixel value in full detail. That produces very large files.

Compression algorithms look for patterns and redundancies in that data. They find smarter ways to represent the same image using less storage space. The two main approaches are lossy compression and lossless compression, and each one makes a different tradeoff between file size and image quality.

Lossy Compression Explained

Lossy compression permanently removes some image data to achieve much smaller file sizes. The algorithm analyzes the image and decides which details the human eye is least likely to notice, then discards them. The result is a smaller file, but you cannot fully recover the original image after compression.

How JPEG Uses Lossy Compression

JPEG is the most common example of lossy compression. It works by converting the image into frequency data using a technique called the Discrete Cosine Transform. High-frequency details like sharp edges and fine textures are reduced more aggressively than low-frequency areas like smooth color gradients. This is why heavily compressed JPEGs tend to show blurry areas and blocky artifacts around edges.

The quality setting in JPEG compression controls how aggressively data is removed. A quality of 90 keeps most details and produces a file that looks nearly identical to the original. A quality of 50 produces a much smaller file with noticeable quality loss. A quality of 10 creates a tiny file that looks quite rough.

When to Use Lossy Compression

Lossy compression is the right choice when you need the smallest possible file size and when some quality loss is acceptable. Common use cases include:

• Photographs for websites and social media
• Product images in online stores
• Photos attached to forms and applications
• Any image where a smaller file size matters more than perfect pixel accuracy

Lossless Compression Explained

Lossless compression reduces file size without throwing away any data. The original image can be reconstructed perfectly from the compressed file. The tradeoff is that lossless files are generally larger than lossy compressed versions of the same image.

How PNG Uses Lossless Compression

PNG uses a combination of a filtering step and the DEFLATE compression algorithm. The filtering step looks at each row of pixels and predicts values based on neighboring pixels, reducing the range of values that need to be stored. Then DEFLATE uses a technique similar to ZIP compression to store those values efficiently. When you open the PNG, the algorithm reverses this process and restores every pixel exactly.

When to Use Lossless Compression

Lossless compression makes sense when image quality cannot be compromised. Good use cases include:

• Screenshots and interface graphics where sharp text matters
• Logos and illustrations with flat colors
• Images that will be edited multiple times
• Medical or scientific images where accuracy is critical

How MB2kB Handles Compression

MB2kB runs entirely in your browser. Your images are never uploaded to any server. All compression happens locally using the browser's built-in Canvas API.

Here is how it works step by step:

1. You upload an image and set a target file size in kilobytes.
2. The tool loads the image into an HTML canvas element.
3. It exports the canvas as a JPEG using an initial quality setting.
4. If the resulting file is still too large, it reduces the quality level and tries again.
5. This iterative process continues until the file size meets your target.
6. The final compressed image is ready for you to download.

This approach uses lossy JPEG compression, which is why it works so well for photographs and scanned documents. If you need to compress an image to 100 KB, for example, the tool automatically finds the highest quality level that still fits within that limit.

When to Use Lossy vs Lossless

The simplest way to decide is to think about what the image will be used for.

Use lossy compression for photographs, profile pictures, scanned documents, and any image that goes on a website or gets uploaded to a form. The quality loss at moderate compression levels is barely visible, and the file size savings are significant.

Use lossless compression for logos, icons, screenshots with text, and images you plan to keep editing. You want every pixel to be exactly right, and the larger file size is an acceptable cost.

Also consider whether you will be compressing the same image multiple times. Each time you save a JPEG, you apply lossy compression again and lose a little more quality. If you need to re-edit and re-save often, keep a lossless original and only produce lossy versions for final delivery.

Choosing the Right Compression Level

Most image compressors give you some control over how aggressively they compress. With MB2kB, you choose a target file size and the tool figures out the right quality level automatically.

A good starting point for most use cases:

• Government form uploads: aim for 50 KB to 100 KB
• Website images: aim for 100 KB to 200 KB for photos
• Email attachments: keep images under 500 KB when possible
• Profile pictures and avatars: 20 KB to 50 KB is usually enough

The key is to compress enough to meet the size requirement while keeping the image clear enough to be useful. A passport photo compressed to 20 KB should still clearly show your face. A scanned document compressed to 100 KB should still be readable.

Want to dig into how different image formats stack up against each other? Check out our guide on JPEG vs PNG vs WebP for a deeper look at format-specific tradeoffs.