Preference of Experience in Image Tone-Mapping: Dataset and Framework for Objective Measures Comparison

A Gabor Feature-Based Quality Assessment Model for the Screen Content Images

Abstract: In this paper, an accurate and efficient full-reference image quality assessment (IQA) model using the extracted Gabor features, called Gabor feature-based model (GFM), is proposed for conducting objective evaluation of screen content images (SCIs). It is well-known that the Gabor filters are highly consistent with the response of the human visual system (HVS), and the HVS is highly sensitive to the edge information. Based on these facts, the imaginary part of the Gabor filter that has odd symmetry and yields edge detection is exploited to the luminance of the reference and distorted SCI for extracting their Gabor features, respectively. The local similarities of the extracted Gabor features and two chrominance components, recorded in the LMN color space, are then measured independently. Finally, the Gabor-feature pooling strategy is employed to combine these measurements and generate the final evaluation score. Experimental simulation results obtained from two large SCI databases have shown that the proposed GFM model not only yields a higher consistency with the human perception on the assessment of SCIs but also requires a lower computational complexity, compared with that of classical and state-of-the-art IQA models. 1 1 The source code for the proposed GFM will be available at http://smartviplab.org/pubilcations/GFM.html .

MC360IQA: A Multi-channel CNN for Blind 360-Degree Image Quality Assessment

Abstract: 360-degree images/videos have been dramatically increasing in recent years. The characteristic of omnidirectional-view results in high resolution of 360-degree images/videos, which makes them difficult to be transported and stored. To deal with the problem, video coding technologies are used to compress the omnidirectional content but they will introduce the compression distortion. Therefore, it is important to study how popular coding technologies affect the quality of 360-degree images. In this paper, we present a study on both subjective and objective quality assessment of compressed virtual reality (VR) images. We first build a compressed VR image quality (CVIQ) database including 16 reference images and 528 compressed ones with three prevailing coding technologies. Then, we propose a multi-channel convolution neural network (CNN) for blind 360-degree image quality assessment (MC360IQA). To be consistent with the visual content seen in the VR device, we project each 360-degree image into six viewport images, which are adopted as inputs of the proposed model. MC360IQA consists of two parts, a multi-channel CNN and an image quality regressor. The multi-channel CNN includes six parallel hyper-ResNet34 networks, where the hyper structure is used to incorporate the features from intermediate layers. The image quality regressor fuses the features and regresses them to final scores. The experimental results show that our model achieves the best performance among the state-of-art full-reference (FR) and no-reference (NR) image quality assessment (IQA) models on the CVIQ database and other available 360-degree IQA database.

Enhanced local tone mapping for detail preserving reproduction of high dynamic range images

Abstract: Enhanced Local Tone Mapping (ELTM) is a flexible tone mapping operator designed to provide a good global and local contrast simultaneously over various test scenes. Also, it has intuitive and decoupled tuning interface, providing the user with full control over final image appearance. ELTM is based on detail/base layer decomposition compressing the base plane in both linear and logarithmic domain. This provides robustness to ELTM, while modified tone compression function provides good local contrast. Results were validated using set of images with various content, brightness and resolution. In this testing ELTM performed as the best tone mapping operator, among 7 state-of-the-art global and local tone mapping operators. Even better overall results are achieved by using proposed brightness control, to handle extreme scenes. Robustness and flexibility to achieve desired appearance makes ELTM suitable for applications where user experience is the primary concern as is the case with consumer electronics products.

Toward the Assessment of Quality of Experience for Asymmetric Encoding in Immersive Media

Abstract: The assessment of Quality of Experience (QoE) for stereoscopic 3-D video is a challenging task, especially in 3-D video compression and transmission applications. The focus of this contribution is the development of a QoE assessment framework, in line with the latest standardization progress in the field of QoE assessment, for understanding the visual effect of asymmetric and symmetric encoding for immersive media. Asymmetric stereoscopic video coding exploits the binocular suppression of the human vision system by representing one of the two views with a lower quality. This processing, while of limited effects on image quality, may influence the overall QoE. Many studies show that the QoE of immersive media such as 3-DTV can be thought as the combination of the perceived visual quality, the perceived depth quality, the visual fatigue, and visual discomfort. In this paper, we aim at: 1) exploiting the concept of preference of experience and protocols recently standardized for characterizing QoE; 2) conducting a case study using these standardized protocols to investigate the factors involving visual discomfort in stereoscopic video sequences with a focus on binocular rivalry; and 3) presenting the results of subjective experiments performed, by using the perceptual quality and preference of experience assessment protocols, for evaluating the impact of symmetrical, asymmetrical, and alternate coding schemes.

Robust high dynamic range color image watermarking method based on feature map extraction

Abstract: In order to protect the copyright of high dynamic range (HDR) images, a novel watermarking method based on feature map extraction is proposed Since the HDR image provides wide dynamic ranges of visible luminance, the correlations of the three RGB channels are much stronger than those of neighbor pixels In order to preserve strong relationships of the three color channels, the Tucker decomposition is used to divide the HDR color image along the three color channels so that three feature maps are extracted The first feature map of the three feature maps is employed to embed watermark for robustness, because it contains most of the energies in the HDR image The first feature map is divided into non-overlapping blocks, and the Schur decomposition is operated on each block to generate a unitary matrix Since the texture or edge remains after the tone mapping operation (TMO) of the HDR image, the stable size relation between the pair-wise coefficients in the unitary matrix is established to embed watermark The experimental results show that the proposed method can efficiently resist different TMOs and common image attacks, outperforming other existing HDR image watermarking methods

Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.

Abstract: Methods of evaluating and comparing the performance of diagnostic tests are of increasing importance as new tests are developed and marketed. When a test is based on an observed variable that lies on a continuous or graded scale, an assessment of the overall value of the test can be made through the use of a receiver operating characteristic (ROC) curve. The curve is constructed by varying the cutpoint used to determine which values of the observed variable will be considered abnormal and then plotting the resulting sensitivities against the corresponding false positive rates. When two or more empirical curves are constructed based on tests performed on the same individuals, statistical analysis on differences between curves must take into account the correlated nature of the data. This paper presents a nonparametric approach to the analysis of areas under correlated ROC curves, by using the theory on generalized U-statistics to generate an estimated covariance matrix.

Making a “Completely Blind” Image Quality Analyzer

Abstract: An important aim of research on the blind image quality assessment (IQA) problem is to devise perceptual models that can predict the quality of distorted images with as little prior knowledge of the images or their distortions as possible. Current state-of-the-art “general purpose” no reference (NR) IQA algorithms require knowledge about anticipated distortions in the form of training examples and corresponding human opinion scores. However we have recently derived a blind IQA model that only makes use of measurable deviations from statistical regularities observed in natural images, without training on human-rated distorted images, and, indeed without any exposure to distorted images. Thus, it is “completely blind.” The new IQA model, which we call the Natural Image Quality Evaluator (NIQE) is based on the construction of a “quality aware” collection of statistical features based on a simple and successful space domain natural scene statistic (NSS) model. These features are derived from a corpus of natural, undistorted images. Experimental results show that the new index delivers performance comparable to top performing NR IQA models that require training on large databases of human opinions of distorted images. A software release is available at http://live.ece.utexas.edu/research/quality/niqe_release.zip.

Photographic tone reproduction for digital images

Abstract: A classic photographic task is the mapping of the potentially high dynamic range of real world luminances to the low dynamic range of the photographic print. This tone reproduction problem is also faced by computer graphics practitioners who map digital images to a low dynamic range print or screen. The work presented in this paper leverages the time-tested techniques of photographic practice to develop a new tone reproduction operator. In particular, we use and extend the techniques developed by Ansel Adams to deal with digital images. The resulting algorithm is simple and produces good results for a wide variety of images.