Image Compression Explained: How It Works and Why It Matters
- 53 minutes ago
- 3 min read
Images are prevalent across the internet, including product photos, blog graphics, satellite imagery, and map encodings. However, high-resolution image files—due to their large file sizes—consume significant bandwidth, slow websites, increase server costs, and require substantial storage space. This is why image compression is so important.
What Is Image Compression?
The process of reducing the file size for an image while keeping an acceptable level of visual quality. The ultimate goal of compression is to store and/or transmit an image using fewer bits.
Compression involves removing redundant (or less obvious) pieces of an image file.
Example:
A raw camera image may be 20MB.
The compressed version of this same image may only be 2MB (or less).
The visual difference between the 2 images could be undetectable to the naked eye.
This ultimately allows web pages to load more quickly and reduces the costs associated with storing images on the server.
Why Image Compression Matters
Faster Website Performance
Large photographs take a long time to load onto a website. Google, for example, uses the speed of a webpage as a part of its ranking system; therefore, if you have photos that are optimized, you will do better on Google, etc.
The Benefits of Compressed Photos are:
Greater Speed with Loading
Better Experience for Users
A Lower Percentage of People Leaving
Increased Rank in Search Engines
Reduced Bandwidth Usage
Every time someone visits a webpage, there is a transfer of data from your web host to the visitor’s computer; each time they click on an image, there is data being transferred.
When you compress your images, you will:
Use less Bandwidth
Save Money on Your Hosting Costs
Have Fewer Problems When People Are Using Mobile Data
This is even more so important when you are talking about a website that is heavily populated with images (e-commerce, blogs, maps, etc.).
Improved Storage Efficiency
Businesses that manage large image libraries—such as media platforms, design agencies, or GIS systems—can save significant storage space using compression.
For example:
Image Type | Original Size | Compressed Size |
High-res photo | 18 MB | 2 MB |
Satellite image | 50 MB | 8 MB |
Web banner | 5 MB | 700 KB |
How Image Compression Works (Technical Overview)
Image compression uses algorithms to identify and eliminate redundancy in pixel data.
Key techniques include:
Transform Coding
The basic method of transform coding is to convert the image data, using algorithms such as DCT (Discrete Cosine Transform), into their respective frequency components. From there, unnecessary frequencies can be removed from the image file.
Used in:
JPEG compression
Quantization
Quantization reduces the value of the color, reducing the data required to represent the color. This process creates a significant majority of lost data during the lossy compression.
Entropy Encoding
Entropy Encoding uses the example of Huffman coding or LZW compression to store the same data more efficiently (by reducing storage space). Examples of this compression method are most prevalent in the PNG and GIF file formats.
Image Compression in Geospatial and GIS Data
Image compression is very important in geospatial and GIS (geographic information systems) applications.
Geospatial and GIS/Geo-spatial systems require massive amounts of image data (e.g., terabytes).
Some examples include:
Terrain data
Raster images
The size of these images can range from gigabytes to terabytes, which is why image compression is essential for all GIS data.
Compression Advantages of GIS Systems
Efficient compression has many benefits when applied to geospatial workflows:
Map Rendering Speed
Compressed imagery can load quicker than non-compressed imagery in web mapping applications, such as:
Interactive map viewers
Location services
Routing Applications
Efficient Transfer of Data
Geospatial data is frequently shared between:
Survey teams
remote sensing platforms
cloud GIS systems
Compression reduces transfer time and network load.
Scalable Cloud Storage
To facilitate unfathomable volumes of imagery in cloud environments, GIS solutions generally use compression to minimize storage costs for those datasets.
Even after all, the file size is reduced with image compression, there is an additional technological benefit that image compression provides to modern-day websites, cloud-based or centralized storage systems, and Geospatial Platforms.
Compression of the image aids in ensuring that the organization can provide high-quality images and graphics; it also allows for an organization's ability to scale its operations without compromising the speed of delivering its data to users through its website functionality.
As the web application and geospatial technology advances and as developers, Data Scientists, and Digital businesses work towards using image optimization and compression techniques, continued mastery of these techniques will be imperative.
For more information or any questions regarding image compression, please don't hesitate to contact us at
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