Objective Image And Video Quality Assessment With Applications

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Title: Objective Image And Video Quality Assessment With Applications
Author: Li, Qiang
Abstract: Objective Image and Video Quality Assessment (IQA /VQA ) aims to automatically measure the quality degradation perceived by the human eyes . It is of fundamental importance to address a wide variety of problems in image and video processing . Based on the availability of the information about the reference image , IQA /VQA models can be classified into Full -reference (FR ) , Reduced -reference (RR ) and No -reference (NR ) IQA /VQA methods . This dissertation focuses on FRIQA /VQA , RRIQA /VQA , as well as their applications in perceptual image coding and video interpolation .First , we propose novel metrics for FRIQA /VQA based on Structural SIMilarity (SSIM ) and the information theoretical weighting . The spatial information weights for image and the spatial -temporal information weights for video are computed respectively in an information theoretical framework . For FRIQA , the spatial information weight is computed as the mutual information using Natural Scene Statistics (NSS ) models . For FRVQA , we incorporate the prior and likelihood models of human visual speed perception to compute the spatial -temporal information weight as a sum of information content and perceptual uncertainty . Moreover , our metrics employ the perceptual weights for multiscale SSIM based on subjective tests .Second , we propose general -purpose RRIQA algorithms which estimate perceptual image quality degradations with partial information about the "perfect -quality" reference image . Considering the dependence in the natural images , joint statistical model is applied to RRIQA , which can handle more general distortions than marginal statistics . A novel RRIQA method is proposed using the statistics of the perceptually and statistically motivated image representation . By using a Gaussian scale mixture statistical model of image wavelet coefficients , we compute a divisive normalization transformation (DNT ) for images and evaluate the quality of a distorted image by comparing a set of reduced -reference statistical features extracted from DNT -domain representations of the reference and distorted images , respectively . This leads to a generic or general -purpose RRIQA method , in which no assumption is made about the types of distortions occurring in the image being evaluated . To address the problem of RRVQA , a novel statistical prior to measure the motion regularity of the natural image sequences is adopted . We investigate the temporal variations of local phase structures in the complex wavelet transform domain . It is observed that natural image sequences exhibit strong prior of temporal motion smoothness , by which local phases of wavelet coefficients can be well predicted from their temporal neighbors . We study how such a statistical regularity is interfered with "unnatural" image distortions and demonstrate the potentials of using temporal motion smoothness measures for RRVQA .Third , we apply our IQA /VQA methods for perceptual image coding and video interpolation . Typically , perceptual image coding algorithms impose perceptual modeling in a preprocessing stage . A perceptual normalization model is often used to transform the original image signal into a perceptually uniform space , in which all the transform coefficients have equal perceptual importance . Standard coding schemes are then applied uniformly to all coefficients . Here we use a different approach , in which we iteratively reallocates the available bits over the image space based on a maximum of minimal structural similarity criterion . We demonstrate the proposed method by incorporating it with the bitplane coding scheme in the set partitioning in hierarchical trees algorithm . Finally , we propose a video frame interpolation method by using the prior knowledge about temporal motion smoothness measured in the complex wavelet domain . This allows us to avoid the time -consuming motion estimation process , and thus largely reduces the computational complexity of video interpolation .
URI: http : / /hdl .handle .net /10106 /1640
Date: 2009-09-16


Objective Image And Video Quality Assessment With Applications. Available electronically from http : / /hdl .handle .net /10106 /1640 .

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