
The aim of the study was to demonstrate and critically discuss the influence of image information on compressibility and image degradation. The influence of image information on image compression was demonstrated on the axial computed tomography images of a head. The standard Joint Photographic Expert Group (JPEG) and JPEG 2000 compression methods were used in compression ratio (CR) and in quality factor (QF) compression modes. Image information was estimated by calculating image entropy, while the effects of image compression were evaluated quantitatively, by file size reduction and by local and global mean square error (MSE), and qualitatively, by visual perception of distortion in high and low contrast test patterns. In QF compression mode, a strong correlation between image entropy and file size was found for JPEG (r=0.87, p < 0.001) and JPEG 2000 (r=0.84, p < 0.001), while corresponding local MSE was constant (4.54) or nearly constant (2.36-2.37), respectively. For JPEG 2000 CR compression mode, CR was nearly constant (1:25), while local MSE varied considerably (2.26 and 10.09). The obtained qualitative and quantitative results clearly demonstrate that image degradation highly depends on image information, which indicates that the degree of image degradation cannot be guaranteed in CR but only in QF compression mode. CR is therefore not a measure of choice for expressing the degree of image degradation in medical image compression. Moreover, even when using QF compression modes, objective evaluation, and comparison of the compression methods within and between studies is often not possible due to the lack of standardization of compression quality scales.
Radiographic Image Enhancement, Humans, Radiographic Image Interpretation, Computer-Assisted, Reproducibility of Results, Artifacts, Data Compression, Tomography, X-Ray Computed, Sensitivity and Specificity, Algorithms
Radiographic Image Enhancement, Humans, Radiographic Image Interpretation, Computer-Assisted, Reproducibility of Results, Artifacts, Data Compression, Tomography, X-Ray Computed, Sensitivity and Specificity, Algorithms
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