title: A method for splitting digital value in radiological image compression.
abstract: A new decomposition method using image splitting and gray-level remapping has been proposed for image compression, particularly for images with high contrast resolution. The effects of this method are especially evident in this radiological image compression study. In these experiments, the impact of this decomposition method was tested on image compression by employing it with two coding techniques on a set of clinically used CT images and several laser film digitized chest radiographs. One of the compression techniques used as zonal full-frame bit-allocation in the discrete cosine transform (DCT) domain, which is an enhanced full-frame DCT technique that has been proven to be an effective technique for radiological image compression. The other compression technique used was vector quantization with pruned tree-structured encoding, which through recent research has also been found to produce a low mean-square error and a high compression ratio. The parameters used in this study were mean-square error and the bit rate required for the compressed file. In addition to these parameters, the differences between the original and reconstructed images were presented so that the specific artifacts generated by both techniques could be discerned through visual perception.
authors.affiliation: Radiology Department, Georgetown University, Washington, DC 20057.
authors.forename: S C
authors.initials: SC
authors.lastname: Lo
authors.forename: E L
authors.initials: EL
authors.lastname: Shen
authors.forename: S K
authors.initials: SK
authors.lastname: Mun
authors.forename: J
authors.initials: J
authors.lastname: Chen
mesh_terms: D001921:Brain / Q000000981:diagnostic imaging; D006801:Humans; D008433:Mathematics; D008962:Models, Theoretical; D011860:Radiography, Abdominal; D013902:Radiography, Thoracic / Q000379:methods; D014057:Tomography, X-Ray Computed / Q000295:instrumentation / Q000379:methods*