Time-varying Volume Compression in Spatio-temporal Domain

نویسندگان

  • Kun Zhao
  • Naohisa Sakamoto
  • Koji Koyamada
چکیده

Data compression is always needed in large-scale time-varying volume visualization. In some recent application cases, the compression method is also required to provide a low-cost decompression process. In this paper, we propose a compression scheme for large-scale time-varying volume data using the spatio-temporal features. With this compression scheme, we are able to provide a proper compression ratio to satisfy many system environments (even a low-spec environment) by setting proper compression parameters. After the compression, we can also provide a low-cost and fast decompression process for the compressed data. Furthermore, we implement a specialized particle-based volume rendering (PBVR) [2] to achieve an accelerated rendering process for the decompressed data. As a result, we confirm the effectiveness of our compression scheme by applying it to the large-scale time-varying turbulent combustion data.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Spatio-temporal analysis of the covid-19 impacts on the using Chicago urban shared bicycles by tensor-based approach

 Cycling is a phenomenon in urban transportation that has the ability to allocate a specific location at any moment in time. Accordingly, spatial analysis of bicycle trips can be accompanied by temporal analysis. The use of a GIS environment is commonly recommended to display the extent of the phenomenon's spatial changes. However, in order to apply and display changes over time, it will requir...

متن کامل

STCS-GAF: Spatio-Temporal Compressive Sensing in Wireless Sensor Networks- A GAF-Based Approach

Routing and data aggregation are two important techniques for reducing communication cost of wireless sensor networks (WSNs). To minimize communication cost, routing methods can be merged with data aggregation techniques. Compressive sensing (CS) is one of the effective techniques for aggregating network data, which can reduce the cost of communication by reducing the amount of routed data to t...

متن کامل

Assessment of Neonate's Congenital Hypothyroidism Pattern Using Poisson Spatio-temporal Model in Disease Mapping under the Bayesian Paradigm during 2011-18 in Guilan, Iran

Background: Congenital Hypothyroidism (CH) is one of the reasons for mental retardation and defective growth in neonates. It can be treated if it is diagnosed early. The congenital hypothyroidism can be diagnosed using newborn screening in the first days after birth. Disease mapping helps to identify high-risk areas of the disease. This study aimed to evaluate the pattern of CH using the Poisso...

متن کامل

Modeling of the Relationships Between Spatio-Temporal Changes of Traffic Volume and Particulate Matter-2.5 Pollutant Concentration Based on Geographically Weighted Regression (GWR) and Inverse Distance Weighting (IDW) Model: A Case Study in Tehran M

Background and Aim: High concentrations of particulate matter-25 (PM2.5) have been the cause of the unhealthiest days in Tehran, Iran in recent years. This study was conducted with the aim of the spatio-temporal analysis of traffic volume and its relationship with PM2.5 pollutant concentrations in Tehran metropolis, Tehran during 2015-2018, using the Geographic Information System (GIS). Materi...

متن کامل

Spatio-Temporal Parameters' Changes in Gait of Male Elderly Subjects

Objectives: The purpose of this study was to compare spatio-temporal gait parameters between elderly and young male subjects. Methods & Materials: 57 able-bodied elderly (72±5.5 years) and 57 healthy young (25±8.5 years) subjects participated in this study. A four segment model consist of trunk, hip, shank, and foot with 10 reflective markers were used to define lower limbs. Kinematic data c...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2013