Optipress

Machine learning based image compression

Different images compressed with the same compression parameters may result in different perceptive quality. Moreover, the same image in different sizes may require different compression strategies to achieve maximum size gain without visible quality loss.

To overcome this, you can use our Optipress JPEG compression algorithm.

• Optipress finds out the best JPG compression approach by analyzing specific image features and current compression parameters.

• A Machine Learning model determines the best compression strategy for this image.

• Quality is then evaluated based on a simulation model of the Human Visual System to achieve optimum compression without perceptive quality deterioration.

By using Optipress, you can get the most out of the JPEG compression format.

Optipress achieves the best results when re-compressing JPEG files and when the image quality is crucial.

Usage

optipress=1	most conservative setting; image quality is prioritised
optipress=2	balanced setting
optipress=3	most aggressive setting; optimised for smaller file size

Images created by Optipress fully comply with baseline JPEG specifications and are compatible with all JPEG encoders.

Examples

Preview	Syntax
	q=85, 543 kB: /sample.li/paris.jpg?force_format=jpeg&q=85 optipress=3, 347 kB: /sample.li/paris.jpg?force_format=jpeg&optipress=3
	q=85, 246 kB: /sample.li/boat.jpg?force_format=jpeg&q=85 optipress=3, 150 kB: /sample.li/boat.jpg?force_format=jpeg&optipress=3