A User Oriented Image Retrieval System using Halftoning BBTC

The objective of this paper is to develop a system for content based image retrieval (CBIR) by accomplishing the benefits of low complexity Ordered Dither Block Truncation Coding based on half toning technique for the generation of image content descriptor. In the encoding step ODBTC compresses an image block into corresponding quantizes and bitmap image. Two image features are proposed to index an image namely co-occurrence features and bitmap patterns which are generated using ODBTC encoded data streams without performing the decoding process. The CCF and BPF of an image are simply derived from the two quantizes and bitmap respectively by including visual codebooks. The proposed system based on block truncation coding image retrieval method is not only convenient for an image compression but it also satisfy the demands of users by offering effective descriptor to index images in CBIR system

Retrieval of Images Using Color, Shape and Texture Features Based on Content

The current study deals with deriving of image feature descriptor by error diffusion based block truncation coding (EDBTC). The image feature descriptor is basically comprised by the two error diffusion block truncation coding, color quantizers and its equivalent bitmap image. The bitmap image distinguish the image edges and textural information of two color quantizers to signify the color allocation and image contrast derived by the Bit Pattern Feature and Color Co-occurrence Feature. Tentative outcome reveal the benefit of proposed feature descriptor as contrast to existing schemes in image retrieval assignment under normal and textural images. The Error-Diffusion Block Truncation Coding method compresses an image efficiently, and at the same time, its consequent compacted information flow can provides an efficient feature descriptor intended for operating image recovery and categorization. As a result, the proposed design preserves an effective candidate for real-time image retrieval applications

Effective Method of Image Retrieval Using BTC with Gabor Wavelet Matrix

emergence of multimedia technology and the rapidly expanding image collections on the database have attracted significant research efforts in providing tools for effective retrieval and management of visual data. The need to find a desired image from a large collection. Image retrieval is the field of study concerned with searching and retrieving digital image from a collection of database .In real images, regions are often homogenous; neighboring pixels usually have similar properties (shape, color, texture). In this paper we proposed novel image retrieval based on Block Truncation Coding (BTC) with Gabor wavelet co-occurrence matrix. For image retrieval the features like shape, color, texture, spatial relation, and correlation and Eigen values are considered. BTC can be used for grayscale as well as for color images. The average precision and recall of all queries are computed and considered for performance analysis

Improved Encoding for Compressed Textures

For the past few decades, graphics hardware has supported mapping a two dimensional image, or texture, onto a three dimensional surface to add detail during rendering. The complexity of modern applications using interactive graphics hardware have created an explosion of the amount of data needed to represent these images. In order to alleviate the amount of memory required to store and transmit textures, graphics hardware manufacturers have introduced hardware decompression units into the texturing pipeline. Textures may now be stored as compressed in memory and decoded at run-time in order to access the pixel data. In order to encode images to be used with these hardware features, many compression algorithms are run offline as a preprocessing step, often times the most time-consuming step in the asset preparation pipeline. This research presents several techniques to quickly serve compressed texture data. With the goal of interactive compression rates while maintaining compression quality, three algorithms are presented in the class of endpoint compression formats. The first uses intensity dilation to estimate compression parameters for low-frequency signal-modulated compressed textures and offers up to a 3X improvement in compression speed. The second, FasTC, shows that by estimating the final compression parameters, partition-based formats can choose an approximate partitioning and offer orders of magnitude faster encoding speed. The third, SegTC, shows additional improvement over selecting a partitioning by using a global segmentation to find the boundaries between image features. This segmentation offers an additional 2X improvement over FasTC while maintaining similar compressed quality. Also presented is a case study in using texture compression to benefit two dimensional concave path rendering. Compressing pixel coverage textures used for compositing yields both an increase in rendering speed and a decrease in storage overhead. Additionally an algorithm is presented that uses a single layer of indirection to adaptively select the block size compressed for each texture, giving a 2X increase in compression ratio for textures of mixed detail. Finally, a texture storage representation that is decoded at runtime on the GPU is presented. The decoded texture is still compressed for graphics hardware but uses 2X fewer bytes for storage and network bandwidth.Doctor of Philosoph

The 1995 Science Information Management and Data Compression Workshop

This document is the proceedings from the 'Science Information Management and Data Compression Workshop,' which was held on October 26-27, 1995, at the NASA Goddard Space Flight Center, Greenbelt, Maryland. The Workshop explored promising computational approaches for handling the collection, ingestion, archival, and retrieval of large quantities of data in future Earth and space science missions. It consisted of fourteen presentations covering a range of information management and data compression approaches that are being or have been integrated into actual or prototypical Earth or space science data information systems, or that hold promise for such an application. The Workshop was organized by James C. Tilton and Robert F. Cromp of the NASA Goddard Space Flight Center

Application and Theory of Multimedia Signal Processing Using Machine Learning or Advanced Methods

This Special Issue is a book composed by collecting documents published through peer review on the research of various advanced technologies related to applications and theories of signal processing for multimedia systems using ML or advanced methods. Multimedia signals include image, video, audio, character recognition and optimization of communication channels for networks. The specific contents included in this book are data hiding, encryption, object detection, image classification, and character recognition. Academics and colleagues who are interested in these topics will find it interesting to read

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

Data Hiding and Its Applications

Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others

Earth imaging with microsatellites: An investigation, design, implementation and in-orbit demonstration of electronic imaging systems for earth observation on-board low-cost microsatellites.

This research programme has studied the possibilities and difficulties of using 50 kg microsatellites to perform remote imaging of the Earth. The design constraints of these missions are quite different to those encountered in larger, conventional spacecraft. While the main attractions of microsatellites are low cost and fast response times, they present the following key limitations: Payload mass under 5 kg, Continuous payload power under 5 Watts, peak power up to 15 Watts, Narrow communications bandwidths (9.6 / 38.4 kbps), Attitude control to within 5°, No moving mechanics. The most significant factor is the limited attitude stability. Without sub-degree attitude control, conventional scanning imaging systems cannot preserve scene geometry, and are therefore poorly suited to current microsatellite capabilities. The foremost conclusion of this thesis is that electronic cameras, which capture entire scenes in a single operation, must be used to overcome the effects of the satellite's motion. The potential applications of electronic cameras, including microsatellite remote sensing, have erupted with the recent availability of high sensitivity field-array CCD (charge-coupled device) image sensors. The research programme has established suitable techniques and architectures necessary for CCD sensors, cameras and entire imaging systems to fulfil scientific/commercial remote sensing despite the difficult conditions on microsatellites. The author has refined these theories by designing, building and exploiting in-orbit five generations of electronic cameras. The major objective of meteorological scale imaging was conclusively demonstrated by the Earth imaging camera flown on the UoSAT-5 spacecraft in 1991. Improved cameras have since been carried by the KITSAT-1 (1992) and PoSAT-1 (1993) microsatellites. PoSAT-1 also flies a medium resolution camera (200 metres) which (despite complete success) has highlighted certain limitations of microsatellites for high resolution remote sensing. A reworked, and extensively modularised, design has been developed for the four camera systems deployed on the FASat-Alfa mission (1995). Based on the success of these missions, this thesis presents many recommendations for the design of microsatellite imaging systems. The novelty of this research programme has been the principle of designing practical camera systems to fit on an existing, highly restrictive, satellite platform, rather than conceiving a fictitious small satellite to support a high performance scanning imager. This pragmatic approach has resulted in the first incontestable demonstrations of the feasibility of remote sensing of the Earth from inexpensive microsatellites