PYRAMID-BASED ERROR-BOUNDED ENCODER - AN EVALUATION ON X-RAY CHEST IMAGES

A novel encoder based on an enhanced Laplacian pyramid is proposed for compression of Medical grey-scale images: major details are prioritiz ed through an adaptive decision rule embedded in a uniform threshold q uantizer with noise feedback. The major benefit of this content-driven feedback quantizer is that significant features are straightforwardly propagated throughout the pyramid, thus enhancing compactness and vis ual quality of the reduced-resolution versions progressively associate d with the code stream. Nevertheless, the reconstruction error is dete rmined only by the size of the quantization step at the base level of the pyramid, thereby making it possible for the maximum absolute recon struction error to be easily and strongly upper-bounded (near-lossless compression), as often required in archiving medical images, for diag nostic and legal purposes. Both lossless and lossy coding show favorab le comparisons with JPEG in objective terms, i.e., compression ratios and distortion plots. Lossy coding outperforms JPEG also subjectively, due to the absence of visual impairments and diagnostic artifacts eve n at very low rates. This feature is also evidenced in a preliminary R OC analysis on a set of X-ray chest images. The pyramid encoder produc es compressed images whose diagnostic quality seems to be comparable, for medium rates, to that of the uncompressed versions, and superior t o that of the JPEG coded versions. (C) 1997 Elsevier Science B.V.