Images frequently make up the majority of the downloaded bytes on a web page and take up a sizable portion of the visual area. Because there is less competition for the client’s bandwidth when there are fewer bytes to download, the browser can download and render meaningful content on the screen more quickly, which can result in some of the largest byte savings and performance gains for your website.
There is no one right way to compress each individual image, making image optimization both an art and a science. On the other hand, there are numerous sophisticated approaches and algorithms that can greatly reduce the size of an image. It takes thorough investigation along many parameters to determine the best settings for your image, including format capabilities, encoded data content, quality, pixel dimensions, and more.
What is image compression?
Image compression is a sort of data compression used to lower the cost of storing or transmitting digital photos. When compared to general data compression techniques used for other digital data, algorithms may benefit from visual perception and the statistical characteristics of picture data.
Optimizing vector images
Scalable Vector Graphics (SVG), an XML-based image format for two-dimensional graphics, is supported by all current browsers. The SVG markup can be integrated within the page itself or used as an external resource. SVG files can be created by the majority of vector-based graphics programs or manually in your preferred text editor.
Types of Image Compression
In order to reduce the size of an image, compression techniques are used. There are two popular types of compression:
- Lossy compression: cuts down on file size by getting rid of redundant material. Although this form of compression can reduce the size of an image file, the quality is sacrificed. Once a file has been compressed, the deleted data cannot be recovered. You should always retain a master copy in the best condition possible to prevent data loss.
- lossless compression: Quality is prioritised over file size in lossless compression. This method keeps the quality high, allowing you to later restore the file if necessary. This method cannot, however, drastically reduce file size.
Some tips and techniques
Following are some pointers and methods to have in mind as you work on picture optimization:
- Prefer Vector Formats: Choose vector formats instead of raster ones since they work better with high-resolution devices and are scale- and resolution-independent.
- Minify and compress SVG assets: XML markup generated by the majority of drawing software frequently contains extraneous metadata that can be eliminated. Ensure that your servers are set up to use GZIP compression for SVG assets.
- Prefer WebP or AVIF: Choose WebP or AVIF over earlier raster formats because these picture types are typically much smaller.
- Choose best raster image format: Choose the appropriate raster image format by evaluating your functional needs and choosing the best option for each asset.
- Experiment with optional quality: Try different raster formats with different quality levels; don’t be scared to drop down the “quality” parameters; the results are frequently excellent and the byte savings are substantial.
- Remove unnecessary image metadata: Many raster images contain extraneous asset metadata, such as geolocation and camera data. Use the right tools to remove this data.
- Serve scaled images: Serve scaled photos by resizing the images to a size that is as close as possible to their “natural” size. Pay great attention to large photos in particular because when downsized, they have the biggest overhead!
- Use automated tools: Invest in automated infrastructure and technologies to make sure that all of your picture assets are always optimised.
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