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[Lecture Notes in Computer Science] Algorithms and Architectures for Parallel Processing Volume 11335 (18th International Conference, ICA3PP 2018, Guangzhou, China, November 15-17, 2018, Proceedings, Part II) || SMIM: Superpixel Mutual Information Measurement for Image Quality Assessment
摘要： The image quality assessment (IQA) is a fundamental problem in signal processing that aims to measure the objective quality of an image by designing a mathematical model. Most full-reference (FR) IQA methods use ?xed sliding windows to obtain structure information but ignore the variable spatial con?guration information. In this paper, we propose a novel full-reference IQA method, named “superpixel normalized mutual information (SMIM)” based on the perspective of variable receptive ?eld and information entropy. First, we ?nd that consistence relationship exists between the information ?delity and human visual of individuals. Thus, we reproduce the human visual system (HVS) to semantically divide the image into multiple patches via superpixel segmentation. Then the weights of each image patches are adaptively calculated via its information volume. We veri?ed the e?ectiveness of SMIM by applying it to data from the TID2008 database and data generated using some real application scenarios. Experiments show that SMIM outperforms some state-of-the-art FR IQA algorithms, including visual information ?delity (VIF).
关键词： Superpixel segmentation,Mutual information,Image quality assessment
更新于2025-09-04 15:30:14
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[IEEE 2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX) - Cagliari (2018.5.29-2018.6.1)] 2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX) - A Hybrid Quality Metric for Non-Integer Image Interpolation
摘要： A great need of High-Resolution (HR) images has boosted the development of interpolation techniques. However, it is still a challenging task to objectively evaluate the perceptual quality of interpolated images, especially when the interpolation factor is a non-integer. To address this issue, we propose a hybrid quality metric for non-integer image interpolation that combines both reduced-reference and no-reference philosophies. To validate the proposed metric, we construct a non-integer interpolated image database and conduct a subjective user study to collect subjective opinions for each image. Experiments on the new database show that the proposed metric outperforms previous methods by a large margin.
关键词： high-resolution images,perceptual image processing,Image quality assessment,image interpolation
更新于2025-09-04 15:30:14
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[IEEE 2018 - 3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON) - Helsinki (2018.6.3-2018.6.5)] 2018 - 3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON) - CHANNEL-MISMATCH DETECTION ALGORITHM FOR STEREOSCOPIC VIDEO USING CONVOLUTIONAL NEURAL NETWORK
摘要： Channel mismatch (the result of swapping left and right views) is a 3D-video artifact that can cause major viewer discomfort. This work presents a novel high-accuracy method of channel-mismatch detection. In addition to the features described in our previous work, we introduce a new feature based on a convolutional neural network; it predicts channel-mismatch probability on the basis of the stereoscopic views and corresponding disparity maps. A logistic-regression model trained on the described features makes the ?nal prediction. We tested this model on a set of 900 stereoscopic-video scenes, and it outperformed existing channel-mismatch detection methods that previously served in analyses of full-length stereoscopic movies.
关键词： machine learning,channel mismatch,quality assessment,convolutional neural networks,Stereoscopic video
更新于2025-09-04 15:30:14