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/.

/pdf/image-quality-assessment-from-error-visibility-to-structural-1rlwcqe34t.pdf

Image quality assessment: from error visibility to structural similarity

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.

http://ahvazdownload.persiangig.com/document/article/39.pdf

A wavelet tour of signal processing

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.

/pdf/image-to-image-translation-with-conditional-adversarial-5058t24et2.pdf

Image-to-Image Translation with Conditional Adversarial Networks

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.

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

Phd by thesis

Introduction to Digital Video Processing

The Texas active vision testbed (TAVT) represents the most recent stage of an ongoing design process that weighed a large number of alternatives, for both hardware and software to create a flexible and precise tool for active vision research. In this paper, we describe this platform and our ongoing research employing this tool. The platform is used in the development of depth recovery algorithms to extend conventional active vision techniques, such as variable baseline stereo and active focus control, as well as support research in the active control of a vergent stereo geometry. >

The Texas active vision testbed

In this rather informal paper and talk I will discuss my own experiences, feelings and evolution as an Image Processing and Digital Video educator trying to navigate the Deep Learning revolution. I will discuss my own ups and downs of trying to deal with extremely rapid technological changes, and how I reacted to, and dealt with consequent dramatic changes in the relevance of the topics I’ve taught for three decades. I arranged the discussion in terms of the stages, over time, of my progression dealing with these sea changes.

Weeping and Gnashing of Teeth: Teaching Deep Learning in Image and Video Processing Classes

We propose a no reference (NR) video quality assessment (VQA) model. Recently, ‘completely blind’ still picture quality analyzers have been proposed that do not require any prior training on, or exposure to, distorted images or human opinions of them. We have been trying to bridge an important but difficult gap by creating a ‘completely blind’ VQA model. The principle of this new approach is founded on intrinsic statistical regularities that are observed in natural vidoes. This results in a video ‘quality analyzer’ that can predict the quality of distorted videos without any external knowledge about the pristine source, anticipated distortions or human judgments. Hence, the model is zero shot. Experimental results show that, even with such paucity of information, the new VQA algorithm performs better than the full reference (FR) quality measure PSNR on the LIVE VQA database. It is also fast and efficient. We envision that the proposed method is an important step towards making real time monitoring of ‘completely blind’ video quality feasible.

Zero shot prediction of video quality using intrinsic video statistics

The asymptotic behavior of the dual filters associated with biorthogonal spline wavelet (BSW) systems and general biorthogonal Coifman wavelet (GBCW) systems are studied. As the order of the wavelet systems approaches infinity, the magnitude responses of the dual filters in the BSW systems either diverge or converge to some nonideal frequency responses. However, the synthesis filters in the GBCW systems converge to an ideal halfband lowpass filter without exhibiting any Gibbs-like phenomenon, and a subclass of the analysis filters also converge to an ideal halfband lowpass filter but with a one-sided Gibbs-like behavior. The two approximations of the ideal lowpass filter by the filter associated with a Daubechies orthonormal wavelet and by the synthesis filter in a GBCW system of the same order are compared. Such a study of the asymptotic behaviors of wavelet systems provides insightful characterization of these systems and systematic assessment and global comparison of different wavelet systems.

Alan C. Bovik

Papers

Introduction to Digital Video Processing

The Texas active vision testbed

Weeping and Gnashing of Teeth: Teaching Deep Learning in Image and Video Processing Classes

Zero shot prediction of video quality using intrinsic video statistics

On asymptotic convergence of the dual filters associated with two families of biorthogonal wavelets