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Title: Human visual system informed perceptual quality assessment models for compressed medical images.
Author: Oh, Joonmi.
Awarding Body: University of Birmingham
Current Institution: University of Birmingham
Date of Award: 2000
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Hospital and clinical environments are rapidly moving toward the digital capture, processing, storage, and transmission of medical images. X-ray cardio-angiograms are used to observe coronary blood flow, diagnose arterial disease and perform coronary angioplasty or bypass surgery. The digital storage and transmission of these cardiovascular images has significant potential to improve patient care. For example, digital images enable electronic archiving, network transmission and useful manipulation of diagnostic information such as image enhancement. The efficient compression of medical images is tremendously important for economical storage and fast transmission, since digitised medical images must be of high-quality, requiring high-resolution and having a large volume in general. The use of lossily compressed images has created a need for the development of objective quality assessment metrics I measuring perceived subjective opinions by viewers for optimal compression rate/distortion trade-off. Quality assessment metrics, based on models of the human visual system, have more accurately predicted perceived quality than traditional error-based objective quality metrics. This thesis presents a proposed Multi-stage Perceptual Quality Assessment (MPQA) model for compressed images. The motivation for the development of a perceptual quality assessment is to measure (in)visible physical differences between original and processed images. MPQA produces visible distortion maps and quantitative error measured informed by considerations of the human visual system. Original and decompressed images are decomposed into different spatial frequency bands and orientations modelling the human cortex. Contrast errors are calculated for each frequency and orientation, and masked as a function of contrast sensitivity and background uncertainty. Spatially masked contrast error measurements are made across frequency bands and orientations to produce a single Perceptual Distortion Visibility Map (PDVM). A Perceptual Quality Rating (PQR) is calculated from the PDVM and transformed into a one to five scale for direct comparison with the Mean Opinion Score (MOS), generally used in subjective rating. For medical applications, acceptable decompressed medical images might be those which are perceptually pleasing, contain no visible artefacts and have no loss in diagnostic content. To investigate this problem, clinical tests identifying diagnostically acceptable image reconstructions is performed and demonstrates that the proposed perceptual quality rating method has better agreement with observers' responses than objective error measurement methods. The vision models presented in the thesis are also implemented in the thresholding and quantisation stages of a compression algorithm. An HVS-informed perceptual thresholding and quantisation method is also shown to produce improved compression ratio performance with less visible distortions.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Digital; Wavelet Pattern recognition systems Pattern perception Image processing