Low bandwidth, image transmission amateur microsatellites

Some recent amateur packet satellites carry open access digital store- and-forward transponders which implement common communication protocols known as PACSAT PROTOCOL SUITE. These standard protocols have improved a "friendly" interaction of different users of packet satellites throughout the world, hence, making packet satellites a more realistic means of communication. Application developments using packet satellites have resulted in an interesting electronic-mail network for medical applications, the Health-Net, where medical professionals in developing countries exchange information with their counterparts. The introduction of a higher rate of data transmission at 9600 baud rate compared to the traditional 1200 baud rate has improved the performance of these satellites. However, this new rate demands some modifications to the existing standard radio receivers and transmitters widely used. In particular, in view of the fact that, digital image technology has transformed microcomputers into powerful visual communication tools, this type of networks can be used for visual communications. Unfortunately, due to the orbit mechanics of satellites involved, the nature of communication protocols and the speed of data transmission currently available, transmission of image data through such networks is difficult in terms of transmission time. This thesis describes the application development of still-continuous tone image transmissions for visual communications, through such networks. It focuses on how to start a packet satellite transmission ground-station, and minimising the transmission time required for image data uploading and downloading, by compressing image data to remove visually insignificant data in the images. Image compression techniques, the internationally recognised JPEG compression technique and a novel compression technique based on FRACTAL, which are known to achieve higher compression ratios are used and compared in this work. Although expensive, FRACTAL compression technique has many advantages over the JPEG compression technique. However, owing to the cost effectiveness of the JPEG compression technique, it is recommended in this thesis for image compression application through Health-Net communication network

A Review on Different Video Coding Standards

Social and network computing demands effective, offering and sparing of image data, which has dependably been an incredible test. Individuals are imparting, transmitting and putting away a great many images every moment. Video coding is a process of compressing and decompressing a digital video signal. The transmission of large size video is facing limitation due to the limited bandwidth and storage capacity. The solution for this is the video compression. In video coding for compression, the basic idea is to exploit redundant data. High Efficiency Video Coding (HEVC) is currently being prepared as the newest video coding standard of the ITU-T Video Coding Experts Group and the ISO/IEC Moving Picture Experts Group. The fundamental goal of the HEVC standardization effort is to enable significantly improved compression performance relative to existing standards. Thus, this paper reviews various standards and techniques and highlight the need for compression. DOI: 10.17762/ijritcc2321-8169.160414

Fractal Image Compression on MIMD Architectures II: Classification Based Speed-up Methods

Since fractal image compression is computationally very expensive, speed-up techniques are required in addition to parallel processing in order to compress large images in reasonable time. In this paper we discuss parallel fractal image compression algorithms suited for MIMD architectures which employ block classification as speed-up method

A Review on Block Matching Motion Estimation and Automata Theory based Approaches for Fractal Coding

Fractal compression is the lossy compression technique in the field of gray/color image and video compression. It gives high compression ratio, better image quality with fast decoding time but improvement in encoding time is a challenge. This review paper/article presents the analysis of most significant existing approaches in the field of fractal based gray/color images and video compression, different block matching motion estimation approaches for finding out the motion vectors in a frame based on inter-frame coding and intra-frame coding i.e. individual frame coding and automata theory based coding approaches to represent an image/sequence of images. Though different review papers exist related to fractal coding, this paper is different in many sense. One can develop the new shape pattern for motion estimation and modify the existing block matching motion estimation with automata coding to explore the fractal compression technique with specific focus on reducing the encoding time and achieving better image/video reconstruction quality. This paper is useful for the beginners in the domain of video compression

The Space and Earth Science Data Compression Workshop

This document is the proceedings from a Space and Earth Science Data Compression Workshop, which was held on March 27, 1992, at the Snowbird Conference Center in Snowbird, Utah. This workshop was held in conjunction with the 1992 Data Compression Conference (DCC '92), which was held at the same location, March 24-26, 1992. The workshop explored opportunities for data compression to enhance the collection and analysis of space and Earth science data. The workshop consisted of eleven papers presented in four sessions. These papers describe research that is integrated into, or has the potential of being integrated into, a particular space and/or Earth science data information system. Presenters were encouraged to take into account the scientists's data requirements, and the constraints imposed by the data collection, transmission, distribution, and archival system

FRACTAL COMPRESSION TECHNIQUE FOR COLOR IMAGES USING VARIABLE BLOCK

The main intention of Fractal Image Compression is to reduce the size of image and maintain good level of their reconstructed image. A major issue in Fractal Image Compression is decrease in image quality, compression ratio and PSNR. To overcome these issues we employ Fractal transformation with entropy coding. There are two phases in the proposed approach. In the first phase color images are separated into three RGB planes using variable range block size. In second phase by applying the inverse transform and iterative functions the image is restored. It is observed that the results are improving in fractal compression for both gray images as well as color images. In this work high CR and PSNR is observed compared to fixed block range and other existing methods. The proposed work yields better CR of 20 and high PSNR

Investigation of the effects of image compression on the geometric quality of digital protogrammetric imagery

We are living in a decade, where the use of digital images is becoming increasingly important. Photographs are now converted into digital form, and direct acquisition of digital images is becoming increasing important as sensors and associated electronics. Unlike images in analogue form, digital representation of images allows visual information to· be easily manipulated in useful ways. One practical problem of the digital image representation is that, it requires a very large number of bits and hence one encounters a fairly large volume of data in a digital production environment if they are stored uncompressed on the disk. With the rapid advances in sensor technology and digital electronics, the number of bits grow larger in softcopy photogrammetry, remote sensing and multimedia GIS. As a result, it is desirable to find efficient representation for digital images in order to reduce the memory required for storage, improve the data access rate from storage devices, and reduce the time required for transfer across communication channels. The component of digital image processing that deals with this problem is called image compression. Image compression is a necessity for the utilisation of large digital images in softcopy photogrammetry, remote sensing, and multimedia GIS. Numerous image Compression standards exist today with the common goal of reducing the number of bits needed to store images, and to facilitate the interchange of compressed image data between various devices and applications. JPEG image compression standard is one alternative for carrying out the image compression task. This standard was formed under the auspices ISO and CCITT for the purpose of developing an international standard for the compression and decompression of continuous-tone, still-frame, monochrome and colour images. The JPEG standard algorithm &Us into three general categories: the baseline sequential process that provides a simple and efficient algorithm for most image coding applications, the extended DCT-based process that allows the baseline system to satisfy a broader range of applications, and an independent lossless process for application demanding that type of compression. This thesis experimentally investigates the geometric degradations resulting from lossy JPEG compression on photogrammetric imagery at various levels of quality factors. The effects and the suitability of JPEG lossy image compression on industrial photogrammetric imagery are investigated. Examples are drawn from the extraction of targets in close-range photogrammetric imagery. In the experiments, the JPEG was used to compress and decompress a set of test images. The algorithm has been tested on digital images containing various levels of entropy (a measure of information content of an image) with different image capture capabilities. Residual data was obtained by taking the pixel-by-pixel difference between the original data and the reconstructed data. The image quality measure, root mean square (rms) error of the residual was used as a quality measure to judge the quality of images produced by JPEG(DCT-based) image compression technique. Two techniques, TIFF (IZW) compression and JPEG(DCT-based) compression are compared with respect to compression ratios achieved. JPEG(DCT-based) yields better compression ratios, and it seems to be a good choice for image compression. Further in the investigation, it is found out that, for grey-scale images, the best compression ratios were obtained when the quality factors between 60 and 90 were used (i.e., at a compression ratio of 1:10 to 1:20). At these quality factors the reconstructed data has virtually no degradation in the visual and geometric quality for the application at hand. Recently, many fast and efficient image file formats have also been developed to store, organise and display images in an efficient way. Almost every image file format incorporates some kind of compression method to manage data within common place networks and storage devices. The current major file formats used in softcopy photogrammetry, remote sensing and · multimedia GIS. were also investigated. It was also found out that the choice of a particular image file format for a given application generally involves several interdependent considerations including quality; flexibility; computation; storage, or transmission. The suitability of a file format for a given purpose is · best determined by knowing its original purpose. Some of these are widely used (e.g., TIFF, JPEG) and serve as exchange formats. Others are adapted to the needs of particular applications or particular operating systems

Distributed video through telecommunication networks using fractal image compression techniques

The research presented in this thesis investigates the use of fractal compression techniques for a real time video distribution system. The motivation for this work was that the method has some useful properties which satisfy many requirements for video compression. In addition, as a novel technique, the fractal compression method has a great potential. In this thesis, we initially develop an understanding of the state of the art in image and video compression and describe the mathematical concepts and basic terminology of the fractal compression algorithm. Several schemes which aim to the improve of the algorithm, for still images are then examined. Amongst these, two novel contributions are described. The first is the partitioning of the image into sections which resulted insignificant reduction of the compression time. In the second, the use of the median metric as alternative to the RMS was considered but was not finally adopted, since the RMS proved to be a more efficient measure. The extension of the fractal compression algorithm from still images to image sequences is then examined and three different schemes to reduce the temporal redundancy of the video compression algorithm are described. The reduction in the execution time of the compression algorithm that can be obtained by the techniques described is significant although real time execution has not yet been achieved. Finally, the basic concepts of distributed programming and networks, as basic elements of a video distribution system, are presented and the hardware and software components of a fractal video distribution system are described. The implementation of the fractal compression algorithm on a TMS320C40 is also considered for speed benefits and it is found that a relatively large number of processors are needed for real time execution

Proceedings of the Scientific Data Compression Workshop

Continuing advances in space and Earth science requires increasing amounts of data to be gathered from spaceborne sensors. NASA expects to launch sensors during the next two decades which will be capable of producing an aggregate of 1500 Megabits per second if operated simultaneously. Such high data rates cause stresses in all aspects of end-to-end data systems. Technologies and techniques are needed to relieve such stresses. Potential solutions to the massive data rate problems are: data editing, greater transmission bandwidths, higher density and faster media, and data compression. Through four subpanels on Science Payload Operations, Multispectral Imaging, Microwave Remote Sensing and Science Data Management, recommendations were made for research in data compression and scientific data applications to space platforms