JPEG2000 extensions for bit plane coding of floating point data

Summary form only given. Modern image compression standards such as JPEG 2000 are only defined to operate on integer data and, thus, they pose a problem if data need compressing. The typical way to handle floating point data is to do an initial quantization. This approach allows standard techniques to be used on the quantized data and may be acceptable to researchers due to the irreversible data loss. Another compression approach is through the use of strictly lossless methods such as LZW based techniques. The disadvantages of this approach include low compression ratios, no capability for lossy compression, and low flexibility of the compressed data stream. Extensions to the JPEG2000 standard were proposed that allow efficient floating point data coding. These extensions have the advantage of maintaining desirable properties of JPEG2000, including flexible embedded bit streams, lossy and lossless compression image scalability. Bit plane coding is needed for an overall floating point algorithm and can be applied when acceptable wavelet and color transforms are derived. The derivation of the floating point bit plane coding algorithms considers only the narrow problem of JPEG2000. The proposed approach for bit plane coding represents floating point values as "big integers" and codes these integers directly as in JPEG2000. A separate eligibility pass every several bit planes was introduced to lower the number of coefficients coded in each coding pass resulting in improved efficiency.