Computationally efficient lossless image coder

Lossless coding of image data has been a very active area of research in the field of medical imaging, remote sensing and document processing/delivery. While several lossless image coders such as JPEG and JBIG have been in existence for a while, their compression performance for encoding continuous-tone images were rather poor. Recently, several state of the art techniques like CALIC and LOCO were introduced with significant improvement in compression performance over traditional coders. However, these coders are very difficult to implement using dedicated hardware or in software using media processors due to their inherently serial nature of their encoding process. In this work, we propose a lossless image coding technique with a compression performance that is very close to the performance of CALIC and LOCO while being very efficient to implement both in hardware and software. Comparisons for encoding the JPEG- 2000 image set show that the compression performance of the proposed coder is within 2 - 5% of the more complex coders while being computationally very efficient. In addition, the encoder is shown to be parallelizabl at a hierarchy of levels. The execution time of the proposed encoder is smaller than what is required by LOCO while the decoder is 2 - 3 times faster that the execution time required by LOCO decoder.