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.

Generalized coiflets: a new family of orthonormal wavelets

Abstract: We generalize an existing family of wavelets, coiflets, by replacing the zero-centered vanishing moment condition on scaling functions by a nonzero-centered one in order to obtain a novel class of compactly supported orthonormal wavelets (we call them generalized coiflets). This generalization offers an additional free parameter i.e., the center of mass of the scaling function, which can be tuned to obtain improved characteristics of the resulting wavelet system such as near-symmetry of the scaling functions and wavelets, near-linear phase of the filter banks, and sampling approximation properties. Therefore, these new wavelets are promising in a broad range of applications in signal processing and numerical analysis.

A high quality, fast inverse halftoning algorithm for error diffused halftones

Abstract: We present an inverse halftoning algorithm for error diffused halftones. At each pixel, the algorithm applies a separable 7/spl times/7 FIR filter parameterized by the computed local horizontal and vertical gradients. All operations are entirely local; only 7 rows of image storage and fewer than 300 operations per pixel are required. The algorithm can be easily implemented in embedded software or hardware. We compare our algorithm with previously reported approaches, and show that it delivers comparable PSNR and subjective quality at a fraction of the computation and memory requirements. A C implementation of the algorithm is available.

On the statistical optimality of locally monotonic regression

Abstract: Locally monotonic regression is a recently proposed technique for the deterministic smoothing of finite-length discrete signals under the smoothing criterion of local monotonicity. Locally monotonic regression falls within a general framework for the processing of signals that may be characterized in three ways: regressions are given by projections that are determined by semimetrics, the processed signals meet shape constraints that are defined at the local level, and the projections are optimal statistical estimates in the maximum likelihood sense. the authors explore the relationship between the geometric and deterministic concept of projection onto (generally nonconvex) sets and the statistical concept of likelihood, with the object of characterizing projections under the family of the p-semi-metrics as maximum likelihood estimates of signals contaminated with noise from a well-known family of exponential densities. >

Study of subject agreement on stereoscopic video quality

Abstract: We describe a study that aims towards enhancing our understanding of the perception of H.264/AVC compressed stereoscopic 3D videos, in particular spatial video quality, depth quality, visual comfort and overall 3D video quality. The results of this study indicate that the human subjects have diverse opinions on depth quality scores but a high agreement on spatial video quality. Their agreement on overall 3D video quality is intermediate relative to that on spatial video quality and depth quality. Based on our analysis, we propose to use separate quality assessment models: spatial video quality models and depth quality models.

Digital reconstruction of three-dimensional serially sectioned optical images

Abstract: The nature of out-of-focus noise is analyzed and linear filtering approaches are demonstrated for minimizing its effect. The analysis is based on concepts of geometrical optics, and takes into account the passage of light through the object. The object is assumed to be nondiffractive and to have low contrast. These assumptions, although not usually met in practice, are not overly restrictive. Experience shows that even dark, diffractive objects show substantial improvement after filtering. Sample images of a pollen grain and a rat pancreas islet are used to demonstrate the efficacy of the technique. >

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