Objective Image Quality Assessment And Its Applications Based On Human Vision System And Distortion Feature Extraction

Among the visual information received by human visual system images arethe matters of primary importance. In the procedures of image processing sys-tem, e.g., acquisition, processing, coding, storage, transmission and reproduction,digital image may be in degradation in visual quality, so evaluating image qual-ity becomes a fundamental job in the field of image processing and computervision. This thesis investigates objective image quality assessment problem fromthe viewpoint of decision fusion, structural feature extraction and multi-scale ge-ometric analysis. Furthermore, the application of general objective image qualityapproach in medical image evaluation is studied and performed. The main workand innovations are listed as follows:1. The research background is extensively reviewed, and some popular im-age quality measures are analyzed and compared from the aspect of distortiondescription and feature extraction. Moreover, the ideal of canonical correlationanalysis is introduced, which keeps the e?ective discriminating information ofmulti-feature as well as eliminates the redundant information inside them tocertain degree. A Supervised Multi-Feature (SMF) full-reference image qualityevaluation algorithm is proposed. Compared with the state-of-the-art image qual-ity metrics, the proposed method improves accuracy and robustness of qualityprediction.2. Propose a novel objective full-reference image quality assessment metricbased on multiscale geometric analysis. The multichannel behavior of the humanvision system is emulated by contourlet transform, a perceptual subband decom-position. The distortion feature and level is emulated by a multi-scale directionaldi?erence model. 3. The HVS model of the low-level perception used in this metric includessubband decomposition, contrast masking, entropy masking, and error pool-ing. Extensive validation experiments are performed on two professional imagedatabases.The proposed method displayed a higher prediction accuracy and ro-bustness across extensive distortion types and a broad range of distortion level,exhibiting a generally better performance.4 .In the error pooling stage, a linear fusion scheme for subband distortionis proposed to trade the frequency properties of the HVS and computation cost.The nonlinear fusion scheme of the Minkowski summation is also implemented forcomparison. Finally, the advantages and limitations of these are compared anddiscussed. Owing to the the employment of the frequency properties of HVS andthe Weber-Fechner law, the linear fusion scheme of subband distortion proved tobe a preferable alternative for the Minkwoski summation.5. Computed tomography (CT) is an essential imaging modality. To solvethe problem of increasing radiation exposure from CT scanner and image qual-ity, general objective image quality methods are applied in CT image qualityevaluation. After analyzing perceptual feature of CT image, several popular ob-jective image quality metrics, which focus on the similar perceptual features, aretested on the CT image of phantom and animals. A lot of experiments are per-formed. Compared with the subjective ratings from two professional radiationphysicians, the complex wavelet-based structural similarity metric presents thebest CT image quality prediction results.