3D/2D object-based coding of head MRI data
We propose a coding system featuring 3D encoding/2D decoding object-based functionalities. Any object of any 2D image of the dataset can be recovered at a finely graded up to lossless quality. Compression is improved by exploiting the full correlation among data samples by means of 3D DWT. A swift access to 2D images is obtained by enabling 2D decoding. Given the index of the image of interest along the z axis, only the concerned portion of the bitstream is decoded, at the desired quality. The selective access to data can be improved by splitting the image in regions corresponding to the different objects. Then, a suitable ordering of the encoded information within the bitstream enables random access to any object at the desired rate. This enables a pseudo-lossless regime, where the diagnostically relevant parts of the image are represented without loss, while a lower quality is assumed to be acceptable for the others. Results show that the proposed system is a good compromise between the gain in compression efficiency provided by 3D systems and the fast access to the data of 2D ones.