Map online system using internet-based image catalogue

Digital maps carry along its geodata information such as coordinate that is important in one particular topographic and thematic map. These geodatas are meaningful especially in military field. Since the maps carry along this information, its makes the size of the images is too big. The bigger size, the bigger storage is required to allocate the image file. It also can cause longer loading time. These conditions make it did not suitable to be applied in image catalogue approach via internet environment. With compression techniques, the image size can be reduced and the quality of the image is still guaranteed without much changes. This report is paying attention to one of the image compression technique using wavelet technology. Wavelet technology is much batter than any other image compression technique nowadays. As a result, the compressed images applied to a system called Map Online that used Internet-based Image Catalogue approach. This system allowed user to buy map online. User also can download the maps that had been bought besides using the searching the map. Map searching is based on several meaningful keywords. As a result, this system is expected to be used by Jabatan Ukur dan Pemetaan Malaysia (JUPEM) in order to make the organization vision is implemented

Data compression techniques applied to high resolution high frame rate video technology

An investigation is presented of video data compression applied to microgravity space experiments using High Resolution High Frame Rate Video Technology (HHVT). An extensive survey of methods of video data compression, described in the open literature, was conducted. The survey examines compression methods employing digital computing. The results of the survey are presented. They include a description of each method and assessment of image degradation and video data parameters. An assessment is made of present and near term future technology for implementation of video data compression in high speed imaging system. Results of the assessment are discussed and summarized. The results of a study of a baseline HHVT video system, and approaches for implementation of video data compression, are presented. Case studies of three microgravity experiments are presented and specific compression techniques and implementations are recommended

Hybrid Neural Network Predictive-Wavelet Image Compression System

This paper considers a novel image compression technique called hybrid predictive wavelet coding. The new proposed technique combines the properties of predictive coding and discrete wavelet coding. In contrast to JPEG2000, the image data values are pre-processed using predictive coding to remove interpixel redundancy. The error values, which are the difference between the original and the predicted values, are discrete wavelet coding transformed. In this case, a nonlinear neural network predictor is utilised in the predictive coding system. The simulation results indicated that the proposed technique can achieve good compressed images at high decomposition levels in comparison to JPEG2000

APPLICATION OF DATA FUSION TO FLUID DYNAMIC DATA

In recent years, there have been improvements in the methods of obtaining fluid dynamic data, which has led to the generation of vast amounts of data. Extracting the useful information from large data sets can be a challenging task when investigating data from a single source. However, most experiments use data from multiple sources, such as particle image velocimetry (PIV), pressure sensors, acoustic measurements, and computational fluid dynamics (CFD), to name a few. Knowing the strengths and weaknesses of each measurement technique, one can fuse the data together to improve the understanding of the problem being studied. Concepts from the data fusion community are used to combine fluid dynamic data from the different data sources. The data is fused using techniques commonly used by the fluid dynamics community, such as proper orthogonal decomposition (POD), linear stochastic estimation (LSE), and wavelet analysis. This process can generate large quantities of data and a method of handling all of the data and the techniques in an efficient manner is required. To accomplish this, a framework was developed that is capable of tracking, storing, and, manipulating data. With the framework and techniques, data fusion can be applied. Data fusion is first applied to a synthetic data set to determine the best methods of fusing data. Data fusion was then applied to airfoil data that was obtained from PIV, CFD, and pressure to test the ideas from the synthetic data. With the knowledge gained from applying fusion to the synthetic data and airfoil data, these techniques are ultimately applied to data for a Mach 0.6 jet obtained from large-window PIV (LWPIV), time-resolved PIV (TRPIV), and pressure. Through the fusion of the different data sets, occlusion in the jet data were estimated within 6% error using a new POD based technique called Fused POD. In addition, a technique called Dynamic Gappy POD was created to fuse TRPIV and LWPIV to generate a large-window time-resolved data set. This technique had less error than other standard techniques for accomplishing this such as pressure-based stochastic estimation. The work presented in this document lays the groundwork for future applications of data fusion to fluid dynamic data. With the success of the work in this document, one can begin to apply the ideas from data fusion to other types of fluid dynamic problems, such as bluff bodies, unsteady aerodynamics, and other. These ideas could be used to help improve understanding in the field of fluid dynamics due to the current limitations of obtaining data and the need to better understand flow phenomena

Hybrid Region-based Image Compression Scheme for Mamograms and Ultrasound Images

The need for transmission and archive of mammograms and ultrasound Images has dramatically increased in tele-healthcare applications. Such images require large amount of' storage space which affect transmission speed. Therefore an effective compression scheme is essential. Compression of these images. in general. laces a great challenge to compromise between the higher compression ratio and the relevant diagnostic information. Out of the many studied compression schemes. lossless . IPl. (i- LS and lossy SPII IT are found to he the most efficient ones. JPEG-LS and SI'll IT are chosen based on a comprehensive experimental study carried on a large number of mammograms and ultrasound images of different sizes and texture. The lossless schemes are evaluated based on the compression ratio and compression speed. The distortion in the image quality which is introduced by lossy methods evaluated based on objective criteria using Mean Square Error (MSE) and Peak signal to Noise Ratio (PSNR). It is found that lossless compression can achieve a modest compression ratio 2: 1 - 4: 1. bossy compression schemes can achieve higher compression ratios than lossless ones but at the price of the image quality which may impede diagnostic conclusions. In this work, a new compression approach called Ilvbrid Region-based Image Compression Scheme (IIYRICS) has been proposed for the mammograms and ultrasound images to achieve higher compression ratios without compromising the diagnostic quality. In I LYRICS, a modification for JPI; G-LS is introduced to encode the arbitrary shaped disease affected regions. Then Shape adaptive SPIT IT is applied on the remaining non region of interest. The results clearly show that this hybrid strategy can yield high compression ratios with perfect reconstruction of diagnostic relevant regions, achieving high speed transmission and less storage requirement. For the sample images considered in our experiment, the compression ratio increases approximately ten times. However, this increase depends upon the size of the region of interest chosen. It is also föund that the pre-processing (contrast stretching) of region of interest improves compression ratios on mammograms but not on ultrasound images