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Image and video compression : fundamentals, techniques, and applications
\"Preface This book is intended primarily for courses in image compression techniques for undergraduate through postgraduate students, research scholars, and engineers working in the field. It presents the basic concepts and technologies in a student-friendly manner. The major techniques in image compression are explained with informative illustrations, and the concepts are evolved from the basics. Practical implementation is demonstrated with MATLAB
Book
Introduction to data compression
Introduction to Data Compression, Third Edition, is a concise and comprehensive guide to data compression. This book introduces the reader to the theory underlying today's compression techniques with detailed instruction for their applications using several examples to explain the concepts. Encompassing the entire field of data compression, it covers lossless and lossy compression, Huffman coding, arithmetic coding, dictionary techniques, context based compression, scalar and vector quantization. It includes all the cutting edge updates the reader will need during the work day and in class. This edition adds new content on the topic of audio compression including a description of the mp3 algorithm, along with a new video coding standard and new facsimile standard explained. It explains in detail established and emerging standards in depth including JPEG 2000, JPEG-LS, MPEG-2, Group 3 and 4 faxes, JBIG 2, ADPCM, LPC, CELP, and MELP. Source code is provided via a companion web site that gives readers the opportunity to build their own algorithms, choose and implement techniques in their own applications. This book will appeal to professionals, software and hardware engineers, students, and to anyone interested in digital libraries and multimedia.
eBook
Handbook of image and video processing
55% new material in the latest edition of this \"must-have for students and practitioners of image & video processing!This Handbook is intended to serve as the basic reference point on image and video processing, in the field, in the research laboratory, and in the classroom.
eBook
Multilinear subspace learning : dimensionality reduction of multidimensional data
\"Due to advances in sensor, storage, and networking technologies, data is being generated on a daily basis at an ever-increasing pace in a wide range of applications, including cloud computing, mobile Internet, and medical imaging. This large multidimensional data requires more efficient dimensionality reduction schemes than the traditional techniques. Addressing this need, multilinear subspace learning (MSL) reduces the dimensionality of big data directly from its natural multidimensional representation, a tensor. Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data gives a comprehensive introduction to both theoretical and practical aspects of MSL for the dimensionality reduction of multidimensional data based on tensors. It covers the fundamentals, algorithms, and applications of MSL. Emphasizing essential concepts and system-level perspectives, the authors provide a foundation for solving many of today's most interesting and challenging problems in big multidimensional data processing. They trace the history of MSL, detail recent advances, and explore future developments and emerging applications.The book follows a unifying MSL framework formulation to systematically derive representative MSL algorithms. It describes various applications of the algorithms, along with their pseudocode. Implementation tips help practitioners in further development, evaluation, and application. The book also provides researchers with useful theoretical information on big multidimensional data in machine learning and pattern recognition. MATLAB source code, data, and other materials are available at www.comp.hkbu.edu.hk/haiping/MSL.html\"-- Provided by publisher
Book
Study on Chain Code Methods for Triangular Grids
Only vertex chain code can be applied to triangular grids, but it has defect in angle adjacent expression. Aimed at the problem of object border representation in triangular grid, three novel chain codes were proposed and compared in character and performance. Firstly, Freeman chain code was extended to triangular grids. For two different triangular elements, the corresponding 12-direction Freeman chain code encoding rules were designed respectively. Secondly, based on the relative direction changes of the contour, the relative direction chain code was proposed. Finally, the edge chain code could be obtained by differentiating the combinations of edges number and internal grids number of the boundary grids. The geometric properties, expressive abilities and compression ratios of three novel chain codes were compared and analyzed. Experiments show that the proposed methods can accurately and completely realize the shape boundary expression of triangular grids. Among them, edge chain owns the best performance, the average code number per grid is 1, and compression ratio can reach 0.75.
Journal Article
Vertebroplasty versus sham procedure for painful acute osteoporotic vertebral compression fractures (VERTOS IV): randomised sham controlled clinical trial
AbstractObjectiveTo assess whether percutaneous vertebroplasty results in more pain relief than a sham procedure in patients with acute osteoporotic compression fractures of the vertebral body.DesignRandomised, double blind, sham controlled clinical trial.SettingFour community hospitals in the Netherlands, 2011-15.Participants180 participants requiring treatment for acute osteoporotic vertebral compression fractures were randomised to either vertebroplasty (n=91) or a sham procedure (n=89).InterventionsParticipants received local subcutaneous lidocaine (lignocaine) and bupivacaine at each pedicle. The vertebroplasty group also received cementation, which was simulated in the sham procedure group.Main outcome measuresMain outcome measure was mean reduction in visual analogue scale (VAS) scores at one day, one week, and one, three, six, and 12 months. Clinically significant pain relief was defined as a decrease of 1.5 points in VAS scores from baseline. Secondary outcome measures were the differences between groups for changes in the quality of life for osteoporosis and Roland-Morris disability questionnaire scores during 12 months’ follow-up.ResultsThe mean reduction in VAS score was statistically significant in the vertebroplasty and sham procedure groups at all follow-up points after the procedure compared with baseline. The mean difference in VAS scores between groups was 0.20 (95% confidence interval −0.53 to 0.94) at baseline, −0.43 (−1.17 to 0.31) at one day, −0.11 (−0.85 to 0.63) at one week, 0.41 (−0.33 to 1.15) at one month, 0.21 (−0.54 to 0.96) at three months, 0.39 (−0.37 to 1.15) at six months, and 0.45 (−0.37 to 1.24) at 12 months. These changes in VAS scores did not, however, differ statistically significantly between the groups during 12 months’ follow-up. The results for secondary outcomes were not statistically significant. Use of analgesics (non-opioids, weak opioids, strong opioids) decreased statistically significantly in both groups at all time points, with no statistically significant differences between groups. Two adverse events occurred in the vertebroplasty group: one respiratory insufficiency and one vasovagal reaction.ConclusionsPercutaneous vertebroplasty did not result in statistically significantly greater pain relief than a sham procedure during 12 months’ follow-up among patients with acute osteoporotic vertebral compression fractures.Trial registrationClinicalTrials.gov NCT01200277.
Journal Article
The association between sarcopenia and osteoporotic vertebral compression refractures
SummarySarcopenia was reported to be significantly associated with osteoporosis. In this study, we reported for the first time that sarcopenia was an independent risk predictor of osteoporotic vertebral compression refractures (OVCRFs). Other risk factors of OVCRFs are low bone mass density T-scores, female sex, and advanced age.IntroductionThe purpose of this study was to investigate the association between osteoporotic vertebral compression refractures (OVCRFs) and sarcopenia, and to identify other risk factors of OVCRFs.MethodsWe evaluated 237 patients with osteoporotic vertebral compression fracture who underwent percutaneous kyphoplasty (PKP) in our hospital from August 2016 to December 2017. To diagnose sarcopenia, a cross-sectional computed tomography (CT) image at the inferior aspect of the third lumbar vertebra (L3) was selected for estimating muscle mass. Grip strength was used to assess muscle strength. Possible risk factors, such as age, sex, body mass index (BMI), bone mineral density (BMD), location of the treated vertebra, anterior-posterior ratio (AP ratio) of the fractured vertebra, cement leakage, and vacuum clefts, were assessed. The multivariable analysis was used to determine the risk factors of OVCRFs.ResultsDuring the follow-up period, OVCRFs occurred in 64 (27.0%) patients. Sarcopenia was present in 48 patients (20.3%), including 21 OVCRFs and 27 non-OVCRFs patients. Sarcopenia was significantly correlated with advanced age, lower BMI, lower BMD, and hypoalbuminemia. Compared with non-sarcopenic patients, sarcopenic patients had higher OVCRFs risk. In univariate analysis, sarcopenia (p = 0.003), female (p = 0.024), advanced age (≥ 75 years; p < 0.001), lower BMD (p < 0.001), lower BMI (p = 0.01), TL junction (vertebral levels at the thoracolumbar junction) (p = 0.01), cardiopulmonary comorbidity (p = 0.042), and hypoalbuminemia (p = 0.003) were associated with OVCRFs. Multivariable analysis revealed that sarcopenia (OR 2.271; 95% CI 1.069–4.824, p = 0.033), lower BMD (OR 1.968; 95% CI 1.350–2.868, p < 0.001), advanced age (≥ 75 years; OR 2.431; 95% CI 1.246–4.744, p = 0.009), and female sex (OR 4.666; 95% CI 1.400–15.552, p = 0.012) were independent risk predictors of OVCRFs.ConclusionsSarcopenia is an independent risk predictor of osteoporotic vertebral compression refractures. Other factors affecting OVCRFs are low BMD T-scores, female sex, and advanced age.
Journal Article
Degenerative cervical myelopathy — update and future directions
Degenerative cervical myelopathy (DCM) is the leading cause of spinal cord dysfunction in adults worldwide. DCM encompasses various acquired (age-related) and congenital pathologies related to degeneration of the cervical spinal column, including hypertrophy and/or calcification of the ligaments, intervertebral discs and osseous tissues. These pathologies narrow the spinal canal, leading to chronic spinal cord compression and disability. Owing to the ageing population, rates of DCM are increasing. Expeditious diagnosis and treatment of DCM are needed to avoid permanent disability. Over the past 10 years, advances in basic science and in translational and clinical research have improved our understanding of the pathophysiology of DCM and helped delineate evidence-based practices for diagnosis and treatment. Surgical decompression is recommended for moderate and severe DCM; the best strategy for mild myelopathy remains unclear. Next-generation quantitative microstructural MRI and neurophysiological recordings promise to enable quantification of spinal cord tissue damage and help predict clinical outcomes. Here, we provide a comprehensive, evidence-based review of DCM, including its definition, epidemiology, pathophysiology, clinical presentation, diagnosis and differential diagnosis, and non-operative and operative management. With this Review, we aim to equip physicians across broad disciplines with the knowledge necessary to make a timely diagnosis of DCM, recognize the clinical features that influence management and identify when urgent surgical intervention is warranted.Degenerative cervical myelopathy is the leading cause of spinal cord dysfunction in adults worldwide. In this Review, the authors provide a comprehensive pathophysiological and clinical overview of the condition to equip physicians across broad disciplines with the knowledge needed for its diagnosis and management.
Journal Article
Semantics-to-Signal Scalable Image Compression with Learned Revertible Representations
Image/video compression and communication need to serve both human vision and machine vision. To address this need, we propose a scalable image compression solution. We assume that machine vision needs less information that is related to semantics, whereas human vision needs more information that is to reconstruct signal. We then propose semantics-to-signal scalable compression, where partial bitstream is decodeable for machine vision and the entire bitstream is decodeable for human vision. Our method is inspired by the scalable image coding standard, JPEG2000, and similarly adopts subband-wise representations. We first design a trainable and revertible transform based on the lifting structure, which converts an image into a pyramid of multiple subbands; the transform is trained to make the partial representations useful for multiple machine vision tasks. We then design an end-to-end optimized encoding/decoding network for compressing the multiple subbands, to jointly optimize compression ratio, semantic analysis accuracy, and signal reconstruction quality. We experiment with two datasets: CUB200-2011 and FGVC-Aircraft, taking coarse-to-fine image classification tasks as an example. Experimental results demonstrate that our proposed method achieves semantics-to-signal scalable compression, and outperforms JPEG2000 in compression efficiency. The proposed method sheds light on a generic approach for image/video coding for human and machines.
Journal Article