Alan C. Bovik

Bio: Alan C. Bovik is an academic researcher from University of Texas at Austin. The author has contributed to research in topics: Image quality & Video quality. The author has an hindex of 102, co-authored 837 publications receiving 96088 citations. Previous affiliations of Alan C. Bovik include University of Illinois at Urbana–Champaign & University of Sydney.

Capturing Video Frame Rate Variations via Entropic Differencing

Abstract: High frame rate videos are increasingly getting popular in recent years, driven by the strong requirements of the entertainment and streaming industries to provide high quality of experiences to consumers. To achieve the best trade-offs between the bandwidth requirements and video quality in terms of frame rate adaptation, it is imperative to understand the effects of frame rate on video quality. In this direction, we devise a novel statistical entropic differencing method based on a Generalized Gaussian Distribution model expressed in the spatial and temporal band-pass domains, which measures the difference in quality between reference and distorted videos. The proposed design is highly generalizable and can be employed when the reference and distorted sequences have different frame rates. Our proposed model correlates very well with subjective scores in the recently proposed LIVE-YT-HFR database and achieves state of the art performance when compared with existing methodologies.

Generalizing a closed-form correlation model of oriented bandpass natural images

Abstract: Building natural scene statistic models is a potentially transformative development for a wide variety of visual applications, ranging from the design of faithful image and video quality models to the development of perceptually optimized image enhancing techniques. Most predominant statistical models of natural images only characterize the univariate distributions of divisively normalized bandpass image responses. Previous efforts towards modeling bandpass natural responses have not focused on finding closed-form quantative models of bivariate natural statistics. Towards filling this gap, Su et al. [1] recently modeled spatially adjacent bandpass image responses over multiple scales; however, they did not consider the effects of spatial distance between the bandpass samples. Here we build on Su et al.'s model and extend their closed-form correlation model to non-adjacent distant bandpass image responses over multiple spatial orientations and scales.

Foveated Image and Video Processing and Search

Abstract: In this article, we present an overview of current techniques used for foveating images and video. We provide a brief introduction to relevant aspects of the human visual system and how they motivate the idea of foveated, or variable resolution, images. We explore the idea of foveation as a perceptually lossless compression scheme and how foveation can be integrated into modern video coding algorithms. We also explore foveation as an efficient processing scheme that is useful when visual resources, such as bandwidth and computation, are constrained. We discuss algorithms for performing visual tasks, such as search and detection, with foveated imaging systems. We examine human behavior when performing similar visual tasks to gain insight into how best to design algorithms for these tasks. We look at some of the more promising applications of foveated video, such as teleoperation, as well as open issues and problems, including fixation selection. We then conclude with what we believe are the future trends of this fascinating area of research.

Basic Tools for Image Fourier Analysis

Abstract: Publisher Summary An understanding of frequency domain and linear filtering concepts is essential to be able to comprehend significant topics such as image and video enhancement, restoration, compression, segmentation, and wavelet-based methods. Exploring these ideas in a 2D setting has the advantage that frequency domain concepts and transforms can be visualized as images, often enhancing the accessibility of ideas. The basic theories in two dimensions (2D) are founded on the same principles. However, there are some extensions. For example, a 2D frequency component, or sinusoidal function, is characterized not only by its location and its frequency of oscillation but also by its direction of oscillation. The 2D DSFT is the basic mathematical tool for analyzing the frequency domain content of 2D discrete-space images. However, it has a major drawback for digital image processing applications: the DSFT of a discrete-space image is continuous in the frequency coordinates; there are uncountably infinite numbers of values to compute. As such, discrete (digital) processing or display in the frequency domain is not possible using the DSFT unless it is modified in some way. Fortunately, this is possible when the image is of finite dimensions.

An Augmented Autoregressive Approach to HTTP Video Stream Quality Prediction.

Abstract: HTTP-based video streaming technologies allow for flexible rate selection strategies that account for time-varying network conditions. Such rate changes may adversely affect the user's Quality of Experience; hence online prediction of the time varying subjective quality can lead to perceptually optimised bitrate allocation policies. Recent studies have proposed to use dynamic network approaches for continuous-time prediction; yet they do not consider multiple video quality models as inputs nor consider forecasting ensembles. Here we address the problem of predicting continuous-time subjective quality using multiple inputs fed to a non-linear autoregressive network. By considering multiple network configurations and by applying simple averaging forecasting techniques, we are able to considerably improve prediction performance and decrease forecasting errors.

Image quality assessment: from error visibility to structural similarity

Abstract: Objective methods for assessing perceptual image quality traditionally attempted to quantify the visibility of errors (differences) between a distorted image and a reference image using a variety of known properties of the human visual system. Under the assumption that human visual perception is highly adapted for extracting structural information from a scene, we introduce an alternative complementary framework for quality assessment based on the degradation of structural information. As a specific example of this concept, we develop a structural similarity index and demonstrate its promise through a set of intuitive examples, as well as comparison to both subjective ratings and state-of-the-art objective methods on a database of images compressed with JPEG and JPEG2000. A MATLAB implementation of the proposed algorithm is available online at http://www.cns.nyu.edu//spl sim/lcv/ssim/.

A wavelet tour of signal processing

Abstract: Introduction to a Transient World. Fourier Kingdom. Discrete Revolution. Time Meets Frequency. Frames. Wavelet Zoom. Wavelet Bases. Wavelet Packet and Local Cosine Bases. An Approximation Tour. Estimations are Approximations. Transform Coding. Appendix A: Mathematical Complements. Appendix B: Software Toolboxes.

Image-to-Image Translation with Conditional Adversarial Networks

Abstract: We investigate conditional adversarial networks as a general-purpose solution to image-to-image translation problems. These networks not only learn the mapping from input image to output image, but also learn a loss function to train this mapping. This makes it possible to apply the same generic approach to problems that traditionally would require very different loss formulations. We demonstrate that this approach is effective at synthesizing photos from label maps, reconstructing objects from edge maps, and colorizing images, among other tasks. Moreover, since the release of the pix2pix software associated with this paper, hundreds of twitter users have posted their own artistic experiments using our system. As a community, we no longer hand-engineer our mapping functions, and this work suggests we can achieve reasonable results without handengineering our loss functions either.

Image-to-Image Translation with Conditional Adversarial Networks

Abstract: We investigate conditional adversarial networks as a general-purpose solution to image-to-image translation problems. These networks not only learn the mapping from input image to output image, but also learn a loss function to train this mapping. This makes it possible to apply the same generic approach to problems that traditionally would require very different loss formulations. We demonstrate that this approach is effective at synthesizing photos from label maps, reconstructing objects from edge maps, and colorizing images, among other tasks. Indeed, since the release of the pix2pix software associated with this paper, a large number of internet users (many of them artists) have posted their own experiments with our system, further demonstrating its wide applicability and ease of adoption without the need for parameter tweaking. As a community, we no longer hand-engineer our mapping functions, and this work suggests we can achieve reasonable results without hand-engineering our loss functions either.

Phd by thesis

Abstract: Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These