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.

Image and Video Quality Assessment.

Abstract: Compounds satisfying four specific requirements, namely: (1) a log P value in the range of from 2.5 to 6, (2) a molecular structure with at least one carboxyl group, (3) a pKa value for the carboxyl group of not less than 2.5 and (4) absence of halo substitution, and nontoxic salts thereof promote absorption of pharmacologically-active substance through the rectum into the bloodstream and are effective to raise the concentration of such active substance in the bloodstream even when the active substance is usually unabsorbable or absorbable through the rectum only with considerable difficulty. The compounds are combined with pharmacologically-active ingredients, with pharmaceutical bases suitable for rectal administration of drugs and with appropriate combinations of both.

Digital restoration of scanning electrochemical microscope images

Abstract: Images obtained from the scanning electrochemical microscope (SECM) have been restored by digital computer techniques. SECM images are inherently blurred by the diffusion process that occurs in the oxidation-reduction reaction at the probe tip. Restoration of an image of the bottom surface of a Ligustrum sinensis leaf as well as the image of a conductive inverse indium tin oxide grid structure is described here. The authors present two techniques for restoring SECM images. The first is an inverse filtering technique and the second is a smoothed Taylor series approximation of the unblurred image via a modification of a procedure given in Rosenfeld and Kak.

Stereo image compression using VPIC

Abstract: A binocular stereo system for images coded by visual pattern image coding (VPIC) is presented and evaluated. The use of VPIC for stereo vision applications is motivated by the capability of its coding primitives to reflect meaningful physical properties of projected real-scene surfaces: high-information edge regions and uniform regions. An algorithm for spatial matching of VPIC primitives is proposed. A dense disparity map is obtained and then used, together with one of the VPIC coded images of the stereo pair, to predict the second stereo image. The proposed stereo system allows a very high compression of the overall stereo information.

Low-complexity velocity estimation in high-speed optical Doppler tomography systems

Abstract: Optical Doppler Tomography (ODT) is a noninvasive 3-D optical interferometric imaging technique that measures static and dynamic structures in a sample. To obtain the dynamic structure, e.g. blood flowing in tissue, a velocity estimation algorithm detects the Doppler shift in the received interference fringe data with respect to the carrier frequency. Previous velocity estimation algorithms use conventional Fourier magnitude techniques that do not provide sufficient frequency resolution in fast ODT systems because of the high data acquisition rates and hence short time series. In this paper, we propose a nonlinear algorithm that uses the phase shift between two successive scans of interference fringe data to give a high-resolution estimate of the Doppler shift. The algorithm detects Doppler shifts of 0.1 to 3 kHz with respect to a 1 MHz carrier. In processing 5 frames/s with 100×100 pixels/frame and 32 samples/pixel, i.e. 1.6 million samples/s, the algorithm requires 26 million multiply-accumulates/s. The algorithm works well at 4 bits/sample. The low complexity and small input data size are well-suited for real-time implementation in software. We provide a mathematical analysis of the Doppler shift resolution by modeling the interference fringe data as an AM-FM signal.

A Progressive Architecture for Learned Fractional Downsampling

Abstract: In many image and video processing applications, the ability to resize by a fractional factor, such as from 1080p to 720p, is essential. However, conventional CNN layers can only be used to alter the resolution of their inputs with integer scale factors. In this paper, we propose a downsampling network architecture that progressively reconstructs residuals at different scales. In particular, the aforementioned problem is solved by combining an upsampling sub-network and a downsampling subnetwork, both with integer scale factor. As an application, we apply the proposed downsampling network to an adaptive bitrate video streaming scenario. We extensively evaluate with different video codecs and upsampling algorithms to show the generality of our model. Our experimental results show that improvements in coding efficiency over the conventional Lanczos downsampling and state-of-the-art methods are attained, measured in different perceptual video quality models on large-resolution test videos.

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