Oriented Correlation Models of Distorted Natural Images With Application to Natural Stereopair Quality Evaluation
Reads0
Chats0
TLDR
A new no-reference stereoscopic/3D IQA framework is developed, dubbed stereoscopic-3D blind image naturalness quality index, which utilizes both univariate and generalized bivariate natural scene statistics (NSS) models.Abstract:
In recent years, bandpass statistical models of natural, photographic images of the world have been used with great success to solve highly diverse problems involving image representation, image repair, image quality assessment (IQA), and image compression. One missing element has been a reliable and generic model of spatial image correlation that reflects the distributions of oriented and relatively oriented spatial structures. We have developed such a model for bandpass pristine images and have generalized it here to also capture the spatial correlation structure of bandpass distorted images. The model applies well to both luminance and depth images. As a demonstration of the usefulness of the generalized model, we develop a new no-reference stereoscopic/3D IQA framework, dubbed stereoscopic/3D blind image naturalness quality index, which utilizes both univariate and generalized bivariate natural scene statistics (NSS) models. We first validate the robustness and effectiveness of these novel bivariate and correlation NSS features extracted from distorted stereopairs, then demonstrate that they are predictive of distortion severity. Our experimental results show that the resulting 3D image quality predictor based in part on the new model outperforms state-of-the-art full- and no-reference 3D IQA algorithms on both symmetrically and asymmetrically distorted stereoscopic image pairs.read more
Citations
More filters
Journal ArticleDOI
Perceptual image quality assessment: a survey
Guangtao Zhai,Xiongkuo Min +1 more
TL;DR: This survey provides a general overview of classical algorithms and recent progresses in the field of perceptual image quality assessment and describes the performances of the state-of-the-art quality measures for visual signals.
Journal ArticleDOI
Unified No-Reference Quality Assessment of Singly and Multiply Distorted Stereoscopic Images
TL;DR: A unified no-reference quality evaluator for SDSIs and MDSIs by learning monocular and binocular local visual primitives (MB-LVPs) to characterize the local receptive field properties of the visual cortex in response to SDS is presented.
Journal ArticleDOI
Dual-Stream Interactive Networks for No-Reference Stereoscopic Image Quality Assessment
Wei Zhou,Zhibo Chen,Weiping Li +2 more
TL;DR: The experimental results show that the proposed StereoQA-Net outperforms state-of-the-art algorithms on both symmetrically and asymmetrically distorted stereoscopic image pairs of various distortion types and can effectively predict the perceptual quality of local regions.
Journal ArticleDOI
Binocular spatial activity and reverse saliency driven no-reference stereopair quality assessment
TL;DR: A new model for no-reference 3D stereopair quality assessment that considers the impact of binocular fusion, rivalry, suppression, and a reverse saliency effect on the perception of distortion, and is thoroughly evaluated on the LIVE 3D image quality database.
Journal ArticleDOI
Blind Deep S3D Image Quality Evaluation via Local to Global Feature Aggregation
TL;DR: This work introduces a novel deep learning scheme for NR S3D IQA in terms of local to global feature aggregation, which is competitive with full-reference S3d IQA metrics and does not estimate the depth from a pair of S2D images.
References
More filters
Journal ArticleDOI
LIBSVM: A library for support vector machines
Chih-Chung Chang,Chih-Jen Lin +1 more
TL;DR: Issues such as solving SVM optimization problems theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail.
Journal ArticleDOI
Image quality assessment: from error visibility to structural similarity
TL;DR: In this article, a structural similarity index is proposed for image quality assessment based on the degradation of structural information, which can be applied to both subjective ratings and objective methods on a database of images compressed with JPEG and JPEG2000.
Journal ArticleDOI
A Tutorial on Support Vector Machines for Pattern Recognition
TL;DR: There are several arguments which support the observed high accuracy of SVMs, which are reviewed and numerous examples and proofs of most of the key theorems are given.
Proceedings Article
A study of cross-validation and bootstrap for accuracy estimation and model selection
TL;DR: The results indicate that for real-word datasets similar to the authors', the best method to use for model selection is ten fold stratified cross validation even if computation power allows using more folds.