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In this paper, we present a new algorithm for blind/no-reference image quality assessment (BIQA/NR-IQA). Most existing measures are “opinion-aware”, demanding human opinion scored images to map image features to them. The task of obtaining human scores of images is, however, commonly thought to be uneconomical, and thus we focus on “opinion free” (OF) quality metrics in this research. By integrating...
In this paper, we propose a fast, effective and practical algorithm for image quality assessment (IQA). Recently, a new free energy theory was revealed in the field of brain science, which illustrates that the human visual system (HVS) always strives to comprehend the input visual signal by reducing the undetermined portions. Inspired by this, our previous work recently designed a valid reduced-reference...
In a typical image communication system, the visual signal presented to the end users may undergo the steps of acquisition, compression and transmission which cause the artifacts of blurring, quantization and noise. However, the researches of image quality assessment (IQA) with multiple distortion types are very limited. In this paper, we first introduce a new multiply distorted image database (MDID2013),...
During the last two decades, image quality assessment has been a major research area, which considerably helps to promote the development of image processing. Following the tremendous success of Structural SIMilarity (SSIM) index in terms of the correlation between the quality predictions and the subjective scores, many improved algorithms have been further exploited, such as Multi-Scale SSIM (MS-SSIM)...
In recent years, while stereoscopic images were becoming widely applied and the corresponding technologies were substantially developed, very few stereoscopic image quality assessment metrics were proposed, especially under the condition that there is no reference image available. This paper proposes a new no-reference stereoscopic image quality assessment algorithm based on the ocular dominance theory...
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