OBJECTIVE SIMILARITY METRICS FOR SCENIC BILEVEL IMAGES

This paper proposes new objective similarity metrics for scenic bilevel images, which are images containing natural scenes such as landscapes and portraits. Though percentage error is the most commonly used similarity metric for bilevel images, it is not always consistent with human perception. Based on hypotheses about human perception of bilevel images, this paper proposes new metrics that outperform percentage error in the sense of attaining significantly higher Pearson and Spearman-rank correlation coefficients with respect to subjective ratings. The new metrics include Adjusted Percentage Error, Bilevel Gradient Histogram and Connected Components Comparison. The subjective ratings come from similarity evaluations described in a companion paper. Combinations of these metrics are also proposed, which exploit their complementarity to attain even better performance.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111058/4/OBJECTIVE SIMILARITY METRICS FOR SCENIC BILEVEL IMAGES.pd

Similarity of Scenic Bilevel Images

This paper has been submitted to IEEE Transaction on Image Processing in May 2015.This paper presents a study of bilevel image similarity, including new objective metrics intended to quantify similarity consistent with human perception, and a subjective experiment to obtain ground truth for judging the performance of the objective similarity metrics. The focus is on scenic bilevel images, which are complex, natural or hand-drawn images, such as landscapes or portraits. The ground truth was obtained from ratings by 77 subjects of 44 distorted versions of seven scenic images, using a modified version of the SDSCE testing methodology. Based on hypotheses about human perception of bilevel images, several new metrics are proposed that outperform existing ones in the sense of attaining significantly higher Pearson and Spearman-rank correlation coefficients with respect to the ground truth from the subjective experiment. The new metrics include Adjusted Percentage Error, Bilevel Gradient Histogram and Connected Components Comparison. Combinations of these metrics are also proposed, which exploit their complementarity to attain even better performance. These metrics and the ground truth are then used to assess the relative severity of various kinds of distortion and the performance of several lossy bilevel compression methods.http://deepblue.lib.umich.edu/bitstream/2027.42/111737/2/Similarity of Scenic Bilevel Images.pdfDescription of Similarity of Scenic Bilevel Images.pdf : Main article ("Similarity of Scenic Bilevel Images"

Perceptual Image Similarity Metrics and Applications.

This dissertation presents research in perceptual image similarity metrics and applications, e.g., content-based image retrieval, perceptual image compression, image similarity assessment and texture analysis. The first part aims to design texture similarity metrics consistent with human perception. A new family of statistical texture similarity features, called Local Radius Index (LRI), and corresponding similarity metrics are proposed. Compared to state-of-the-art metrics in the STSIM family, LRI-based metrics achieve better texture retrieval performance with much less computation. When applied to the recently developed perceptual image coder, Matched Texture Coding (MTC), they enable similar performance while significantly accelerating encoding. Additionally, in photographic paper classification, LRI-based metrics also outperform pre-existing metrics. To fulfill the needs of texture classification and other applications, a rotation-invariant version of LRI, called Rotation-Invariant Local Radius Index (RI-LRI), is proposed. RI-LRI is also grayscale and illuminance insensitive. The corresponding similarity metric achieves texture classification accuracy comparable to state-of-the-art metrics. Moreover, its much lower dimensional feature vector requires substantially less computation and storage than other state-of-the-art texture features. The second part of the dissertation focuses on bilevel images, which are images whose pixels are either black or white. The contributions include new objective similarity metrics intended to quantify similarity consistent with human perception, and a subjective experiment to obtain ground truth for judging the performance of objective metrics. Several similarity metrics are proposed that outperform existing ones in the sense of attaining significantly higher Pearson and Spearman-rank correlations with the ground truth. The new metrics include Adjusted Percentage Error, Bilevel Gradient Histogram, Connected Components Comparison and combinations of such. Another portion of the dissertation focuses on the aforementioned MTC, which is a block-based image coder that uses texture similarity metrics to decide if blocks of the image can be encoded by pointing to perceptually similar ones in the already coded region. The key to its success is an effective texture similarity metric, such as an LRI-based metric, and an effective search strategy. Compared to traditional image compression algorithms, e.g., JPEG, MTC achieves similar coding rate with higher reconstruction quality. And the advantage of MTC becomes larger as coding rate decreases.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113586/1/yhzhai_1.pd

Data-Driven Optimization for Bicycle Station Location in a Small to Medium-Sized City: The Case Study of Cuenca, Ecuador

Bike sharing systems (BSSs) are an important transportation alternative, and station distribution is a key component of these that is driven by user demand and resource constraints. Designing an effective BSS with appropriate station distribution requires a method that consists of steps structured in a flexible, parameterizable, repeatable, and organized way, based on and aligned with proven or accepted standards---particularly in resource-limited environments. This includes data-driven analysis of information relevant to BSS station design from various sources and in different formats. Models and algorithms are used to organize and examine the data, reduce redundant data, standardize factors, and find patterns that can inform the efficient design and implementation of a BSS. The algorithms and models used in the present study provide a data-driven approach to determining effective BSS station distribution in a city. Factor analysis and principal component analysis (PCA) were used as the various sources of data involved in the design of a BSS (i.e., data on traffic, demographic, and land use) can often overlap and/or have redundant data and these techniques allow minimizing superfluous data without losing relevant information. Econometric models were also used to identify the costs of pollutants, with the aim of locating stations in areas where pollution is a problem, and an emission-free BSS might be of greatest benefit. Patterns of potential users and mobility are derived from unsupervised learning algorithms. Finally, the set covering model (SCP), an optimization model for the distribution of stations, is used to define the number of stations in the city and their locations. This model\u27s objective is to minimize costs while still satisfying user demand. Using this data-driven approach can help guide the strategic design and planning of a BSS. A case study using this method was carried out using data from the city of Cuenca, Ecuador, the third most populous city in this developing country. Cuenca is considered a mid-sized city and is a UNESCO World Heritage Site. When compared to the costly Spanish--Ecuadorian consortium that implemented the currently BSS running in Cuenca, applying the proposed data-driven approach to this real-life practical case study resulted in a 70--90\% match in the locations of stations. The consortium had to study the place of implementation in a great amount of depth and obtained a similar design to that obtained in this case study. This demonstrates the potential of the proposed method as a simple, effective, and low-cost method for the strategic planning of BSSs in small and mid-sized cities. The present study provides an affordable solution to the design of BSS station distribution for cities without many resources. Using this method, cities can take advantage of a standardized platform to define a network of stations through an established step-by-step process. The method of BSS design proposed here demonstrates three significant advantages: 1) in-depth knowledge of the area in which a BSS is to be implemented location is not required, as the design can be driven by existing data and can even be adapted to new data sources; 2) implementation is economical as this reduces the need to hire expensive expert personnel with knowledge and experience in implementing BSSs; 3) the method is versatile since it can accept input data of various kinds, which enables the adaptation of the solution to any small or mid-sized city. This method, therefore, provides small and mid-sized resource-limited cities with a simple and cost-effective method to design a BSS that can be tailored to particular contexts and can be adapted to the specific goals of BSS implementation in a given city

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes

SUBJECTIVE SIMILARITY EVALUATION FOR SCENIC BILEVEL IMAGES

In order to provide ground truth for subjectively comparing compression methods for scenic bilevel images, as well as for judging objective similarity metrics, this paper describes the subjective similarity rating of a collection of distorted scenic bilevel images. Unlike text, line drawings, and silhouettes, scenic bilevel images contain natural scenes, e.g., landscapes and portraits. Seven scenic images were each distorted in forty-four ways, including random bit flipping, dilation, erosion and lossy compression. To produce subjective similarity ratings, the distorted images were each viewed by 77 subjects. These are then used to compare the performance of four compression algorithms and to assess how well percentage error and SmSIM work as bilevel image similarity metrics. These subjective ratings can also provide ground truth for future tests of objective bilevel image similarity metrics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111057/4/SUBJECTIVE SIMILARITY EVALUATION FOR SCENIC BILEVEL IMAGES.pd

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order

Scenic bilevel image similarity metrics MATLAB code

This item contains MATLAB code for scenic bilevel image similarity metrics described in the following two papers: (1) Y. Zhai and D.L. Neuhoff, Similarity of Scenic Bilevel Images, to appear in IEEE Transaction on Image Processing, 2016. (2) Y. Zhai, D.L. Neuhoff and T.N. Pappas, Objective Similarity Metrics for Scenic Bilevel Images, IEEE Intl. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), pp. 2793-2797, Florence, Italy, May 2014.http://deepblue.lib.umich.edu/bitstream/2027.42/122736/1/Scenic bilevel image similarity metrics MATLAB code.zipDescription of Scenic bilevel image similarity metrics MATLAB code.zip : MATLAB cod

Building Ownership, Renovation Investments, and Energy Performance—A Study of Multi-Family Dwellings in Gothenburg

The European building stock was renewed at a rapid pace during the period 1950–1975. In many European countries, the building stock from this time needs to be renovated, and there are opportunities to introduce energy efficiency measures in the renovation process. information availability and increasingly available analysis tools make it possible to assess the impact of policy and regulation. This article describes methods developed for analyzing investments in renovation and energy performance based on building ownership and inhabitant socio-economic information developed for Swedish authorities, to be used for the Swedish national renovations strategy in 2019. This was done by analyzing measured energy usage and renovation investments made during the last 30 years, coupled with building specific official information of buildings and resident area characteristics, for multi-family dwellings in Gothenburg (N = 6319). The statistical analyses show that more costly renovations lead to decreasing energy usage for heating, but buildings that have been renovated during the last decades have a higher energy usage when accounting for current heating system, ownership, and resident socio-economic background. It is appropriate to include an affordability aspect in larger renovation projects since economically disadvantaged groups are over-represented in buildings with poorer energy performance