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.

No-reference task performance prediction on distorted LWIR images

Abstract: Recent work on the problem of Image Quality Assessment (IQA) has produced accurate subjective quality evaluators for visible light images. Two such algorithms are the Blind/Referenceless Image Spatial QUality Evaluator (BRISQUE) and the Natural Image Quality Evaluator (NIQE). Both models are useful in that they correlate highly with human visual perception of image quality. Given that other kinds of non-visible light images are also 'natural' projections of the world, and can be distorted thereby reducing the perceived quality, it is of interest to study whether quality prediction on other image modality can find practical use. To this end we have extended the application of modern blind IQA models.

Design and quality assessment of forward and inverse error diffusion halftoning algorithms

Abstract: Digital halftoning is the process by which a continuous-tone image is converted to a binary image, or halftone, for printing or display on binary devices Error diffusion is a halftoning method which employs feedback to preserve the local image intensity and reduce low frequency quantization noise It is a highly nonlinear process, and it is therefore difficult to analyze mathematically In this work, a linear gain model for the quantizer is presented which accurately predicts the edge sharpening and noise shaping effects of error diffusion The model is used to construct a residual image that has a low correlation with the original image By weighting this residual with a model of the human visual system, a measure of the subjective effect of the quantization noise on the viewer is obtained A distortion metric for the halftoning scheme is also computed By characterizing the edge sharpening, noise shaping, and distortion of an error diffusion scheme, objective measures of subjective quality of halftones are obtained This permits the comparison of halftoning schemes We present a new, efficient inverse halftoning scheme for error diffused halftones that produces results comparable to the best current methods, but at a fraction of the computational cost We demonstrate a method of modeling inverse halftoning schemes, and use the model to generate residual images, which we weight with the human visual system model We also compute an effective transfer function for the inverse halftoning scheme By characterizing the degree of blurring and the noise content, we obtain objective measures of subjective quality of inverse halftones This allows competing inverse halftoning algorithms to be compared We further use the linear gain model to design and analyze the performance of applications which include error diffusion We again make use of the model of the human visual system to obtain objective measures of the quality of images produced by these applications

Generically sufficient conditions for exact multichannel blind image restoration

Abstract: We have previously developed an algorithm and sufficient conditions for exact multichannel blind image restoration. In this paper, we use the resultant matrix theorem and techniques of algebraic geometry to prove that the sufficient conditions hold generically given three blurred versions of the same image and some restrictions on the size of the original image. Moreover, the extension to multichannel blind n-dimensional signal restoration is described.

Improved initial approximation and intensity-guided discontinuity detection in visible-surface reconstruction

Abstract: Techniques are described for improving the speed and accuracy of iterative visible-surface reconstruction algorithms. In particular, the importance of obtaining accurate early information is emphasized, both in the initial surface approximation and in the early localization of surface discontinuities. The first of these goals is attained using a simple technique known as constraint expansion, which yields a good initial approximation while accounting for detected discontinuities. The second goal is attained by using the locations of the image irradiance edges as a guide in locating potential discontinuities. Discontinuity detection in later stages of computation is augmented by a double-thresholding strategy and discontinuity backtracking.

Computer-aided diagnosis in breast magnetic resonance imaging.

Abstract: In this paper, we review the role played by breast magnetic resonance imaging in the detection and diagnosis of breast cancer. This is followed by a discussion of clinical decision support systems in medicine and their contributions in breast magnetic resonance imaging interpretation. We conclude by discussing the future of computer-aided diagnosis in breast magnetic resonance imaging. Mt Sinai J Med 78:280–290, 2011. © 2011 Mount Sinai School of Medicine

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