What Is JPG Compression? Principles and How It Works

In the internet age, images are almost everywhere. Whether on websites, social media, or mobile apps, images play a key role in conveying information and attracting attention. However, a large number of high-resolution images presents a challenge: files can become excessively large. To balance visual quality and loading speed, JPG compression (JPEG compression) has become one of the most widely used solutions. This article explores the principles, types, and practical use cases of JPG compression, and how to significantly reduce image file size while maintaining perceived clarity.

1. What is the JPG format?

JPG (or JPEG, short for Joint Photographic Experts Group) is a widely adopted image format. Its main feature lies in using lossy compression algorithms to remove redundant data while retaining details perceptible to the human eye, thus effectively reducing file size.

In other words, the core idea behind JPG is to make the image appear “the same” while using less data.
This contrasts with lossless formats such as PNG or BMP, which preserve every pixel’s information and therefore result in larger files.

2. Core principles of JPG compression

JPG compression is not merely about “removing pixels” or “reducing sharpness”; it is a precise mathematical process based on human visual perception. The workflow can be divided into the following stages:

1. Colour space conversion

JPG compression first converts the image from the RGB colour space (red, green, blue) to YCbCr.

Y represents luminance,
Cb and Cr represent chrominance.

Because the human eye is more sensitive to luminance than to colour variations, compression algorithms discard or approximate more chrominance information.

2. Block processing (8×8 blocks)

The image is divided into multiple 8×8 pixel blocks.
This enables the compression algorithm to analyse local patterns more efficiently and reduces computation for the entire image.

3. Discrete Cosine Transform (DCT)

Each 8×8 block undergoes a mathematical operation known as the Discrete Cosine Transform (DCT).
The DCT converts spatial image data into frequency components, separating areas with rapid colour transitions.

Simply put:

Low-frequency components represent smooth regions (for example, sky or skin),
High-frequency components represent details or noise (for example, texture or edges).

4. Quantisation

This stage is the key to lossy compression.
The algorithm employs a quantisation table to round or approximate high-frequency data, which significantly reduces file size.

For instance, a value of 253 might be approximated as 250. The human eye barely perceives the difference, yet a considerable amount of data is saved.

5. Entropy coding

The final stage uses Huffman coding or arithmetic coding to further compress the remaining data.
This stage is lossless and aims to represent repetitive information using fewer bits.

3. Types of JPG compression

1. Lossy compression

This is the most common form of JPG used on the web and in photographs.
It reduces file size by discarding visually insignificant data.

Advantages: high compression ratios, often exceeding 90 per cent.
Disadvantages: repeated compression results in gradual quality degradation.

2. Lossless compression (Lossless JPEG)

This approach retains all data and is suitable for scenarios requiring high precision, such as medical imaging or scientific computation.
As file sizes remain large, it is not generally used for everyday purposes.

4. Why JPG compression matters

1. Improve page loading speed

Images on web pages often account for more than 60 per cent of total data. Proper compression allows pages to load within seconds, reducing bounce rates and improving conversions.

2. Improve SEO performance

Search engines like Google and Bing consider page load speed a ranking factor.
Compressed images can significantly enhance metrics such as LCP (Largest Contentful Paint) and CLS (Cumulative Layout Shift), thus improving search visibility.

3. Save storage and bandwidth

For content platforms, gallery sites, or e-commerce stores, image compression can considerably reduce CDN and storage costs.

5. How to choose the right compression level

Higher compression ratios lead to more noticeable quality loss. Typical suggestions:

Web display images: quality between 70 and 85;
Photographs or high-definition assets: keep quality above 90;
Thumbnails or preview images: can range from 60 to 70.

The best method is to compare the subjective visual differences before and after compression, rather than relying solely on numerical values.

6. JPG compression and modern formats

With the development of web technologies, newer image formats such as WebP and AVIF have emerged, offering smaller file sizes at comparable visual quality. Nevertheless, JPG remains irreplaceable:

Broad compatibility (supported by nearly all devices),
Mature algorithms and rapid compression,
Still an efficient option for photographic images.

Therefore, JPG compression continues to be a fundamental component of web optimisation.

7. Conclusion: compression is an intelligent balance

The value of JPG compression lies not only in making files smaller but also in achieving an equilibrium between visual experience and data efficiency.
It embodies the perfect combination of image science, mathematical algorithms, and human perception.

If you wish to quickly optimise website images, try online tools such as a Compress JPG tool, which helps maintain quality while improving loading speed and user experience.