JPEG AI targets a wide range of applications such as cloud storage, visual surveillance, autonomous vehicles and devices, image collection storage and management, live monitoring of visual data and media distribution. The main objective is to design a coding solution that offers significant compression efficiency improvement over coding standards in common use at equivalent subjective quality and an effective compressed domain processing for machine learning-based image processing and computer vision tasks. Other key requirements include hardware/software implementation-friendly encoding and decoding, support for 8- and 10-bit depth, efficient coding of images with text and graphics and progressive decoding.

During the 94th JPEG meeting, several activities towards a JPEG AI learning-based coding standard have occurred, notably the release of the Final Call for Proposals for JPEG AI, consolidated with the definition of the Use Cases and Requirements and the Common Training and Test Conditions to assure a fair and complete evaluation of the future proposals.

The final JPEG AI Call for Proposals marks an important milestone being the first time that contributions are solicited towards a learning-based image coding solution. The JPEG AI proposals’ registration deadline is 25 February 2022. There are three main phases for proponents to submit materials, namely, on 10th March for the proposed decoder implementation with some fixed coding model, on 2nd May for the submission of proposals’ bitstreams and decoded images and/or labels for the test datasets, and on 18th July, for the submission of source code for the encoder, decoder, training procedure and the proposal description. The presentation and discussion of the JPEG AI proposals will occur during the 96th JPEG meeting. JPEG AI is a joint standardization project between IEC, ISO and ITU.

To stay informed on JPEG AI activities, please regularly consult the jpeg.org website and/or subscribe to the e-mail reflector.