Quality Evaluation for Compressed Medical Images: Fundamentals

Cosman, Pamela C.

doi:10.1016/b978-012373904-9.50066-0

Cited by 2 publications

(3 citation statements)

References 49 publications

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“…The normalized mean squared error (NMSE) is the most commonly used method to measure the quality changes in compressed images. [6][7][8][9][10][11] The NMSE is a measure of the image difference that is formed by taking the mean of the squared differences between all corresponding pixels in the original and the compressed images. The guidance document for PACS requires that manufacturers report to PDA the NMSE of their lossy compression technique.…”

Section: T He Picture Archiving Andmentioning

confidence: 99%

Quality Degradation in Lossy Wavelet Image Compression

Chen

Chuang

et al. 2003

J Digit Imaging

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The objective of this study was to develop a method for measuring quality degradation in lossy wavelet image compression. Quality degradation is due to denoising and edge blurring effects that cause smoothness in the compressed image. The peak Moran z histogram ratio between the reconstructed and original images is used as an index for degradation after image compression. The Moran test is applied to images randomly selected from each medical modality, computerized tomography, magnetic resonance imaging, and computed radiography and compressed using the wavelet compression at various levels. The relationship between the quality degradation and compression ratio for each image modality agrees with previous reports that showed a preference for mildly compressed images. Preliminary results show that the peak Moran z histogram ratio can be used to quantify the quality degradation in lossy image compression. The potential for this method is applications for determining the optimal compression ratio (the maximized compression without seriously degrading image quality) of an image for teleradiology.

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Section: T He Picture Archiving Andmentioning

confidence: 99%

Quality Degradation in Lossy Wavelet Image Compression

Chen

Chuang

et al. 2003

J Digit Imaging

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show abstract

“…Presentation-subjective quality dimension measures the presentation quality of decompressed images subjectively [1]. These measures are based on observer's subjective perception of reconstructed image quality [24]. They are the most accurate prediction of decompressed image quality.…”

Section: Introductionmentioning

confidence: 99%

“…• Domain task measurements which measure the usefulness of decompressed image for certain task such as Receiver Operating Characteristics (ROC) [1,24]. Technical-objective quality dimension measures technical aspects of image compression [14].…”

Section: Introductionmentioning

confidence: 99%