CALIC stands for Context-Based, Adaptive, Lossless Image Coding, and is an image codec that is made for obtaining a high degree of compression for continuous-tone gray-scaled images. It uses a single pass and self-correcting GAP (gradient adjusted predictor) to compress image efficiently and with a high compression ratio. CALIC puts heavy emphasis on image data modeling, and it makes use of a large number of modeling contexts to condition a nonlinear predictor (gradient-adjusted predictor) and adapt the predictor to varying source statistics. Since 2000, CALIC was considered as a benchmark for lossless compression for continuous-tone images.
Me and my friends (Siddharth and Sanjay) have implemented a basic version of the CALIC compression codec as part of our coursework (Digital Image Processing course – 6th Sem). We’ve maintained a separate blog for this purpose.
To go through the schematic description of CALIC as well as a detailed overview of all the individual components, you can click here. This paper gives an elaborate explanation about the working and the main components in CALIC as well as comparison with other famous image compression formats such as JPEG2000.
Blog Link : – CALIC – UE14CS348 project