Books about Image compression (found 338 titles)

Three-Dimensional Model Analysis and Processing (Advanced Topics in Science and Technology in China)

"Three-Dimensional Model Analysis and Processing" focuses on five hot research directions in 3D model analysis and processing in computer science, i.e., on compression, feature extraction, content-based retrieval, irreversible watermarking and reversible watermarking. The book is based on a wide range of new content, systematic and theoretical, and fully reflects the state-of-the-art in 3D model analysis and processing technologies. This book is intended for researchers, engineers and graduate students working in 3D model analysis and processing. Faxin Yu is an Associate Professor at the School of Aeronautics and Astronautics, Zhejiang University, China; both Zheming Lu and Pinghui Wang are also Professors there; Hao Luo is a Lecturer there.

Image and Video Compression

This book describes the principles of image and video compression techniques and introduces current and popular compression standards, such as the MPEG series. Derivations of relevant compression algorithms are developed in an easy-to-follow fashion. Numerous examples are provided in each chapter to illustrate the concepts. The book includes complementary software written in MATLAB SIMULINK to give readers hands-on experience in using and applying various video compression methods. Readers can enhance the software by including their own algorithms.

Advanced Statistical Steganalysis (Information Security and Cryptography)

Steganography is the art and science of hiding information in inconspicuous cover data so that even the existence of a secret message is kept confidential, and steganalysis is the task of detecting secret messages in covers. This research monograph focuses on the role of cover signals, the distinguishing feature that requires us to treat steganography and steganalysis differently from other secrecy techniques. The main theoretical contribution of the book is a proposal to structure approaches to provably secure steganography according to their implied assumptions on the limits of the adversary and on the nature of covers. A further contribution is the emphasis on dealing with heterogeneity in cover distributions, crucial for security analyses. The author's work complements earlier approaches based on information, complexity, probability and signal processing theory, and he presents numerous practical implications. The scientific advances are supported by a survey of the classical steganography literature; a new proposal for a unified terminology and notation that is maintained throughout the book; a critical discussion of the results achieved and their limitations; and an assessment of the possibility of transferring elements of this research's empirical perspective to other domains in information security. The book is suitable for researchers working in cryptography and information security, practitioners in the corporate and national security domains, and graduate students specializing in multimedia security and data hiding.

Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing

This textbook introduces sparse and redundant representations with a focus on applications in signal and image processing. The theoretical and numerical foundations are tackled before the applications are discussed. Mathematical modeling for signal sources is discussed along with how to use the proper model for tasks such as denoising, restoration, separation, interpolation and extrapolation, compression, sampling, analysis and synthesis, detection, recognition, and more. The presentation is elegant and engaging.

Sparse and Redundant Representations is intended for graduate students in applied mathematics and electrical engineering, as well as applied mathematicians, engineers, and researchers who are active in the fields of signal and image processing.

Data Compression In Imaging (Synthesis Lectures on Image, Video, and Multimedia Processing)

FPGA Based Image Compression: Concepts, Developments and Implementation

The book is pivoted to the usage of the 2-D Discrete Cosine Transform (DCT) technique for image compression, wherein the readers will come across the development of a new and faster 2-D DCT algorithm, and its hardware implementation. It describes the evolution of VHDL codes by implementing DSP Design Architect tools from Mentor Graphics in respect of hardware chip realization. However, efforts are also made simultaneously towards the development of the relevant algorithm in MATLAB platform in order to verify the functionality of the developed VHDL codes. The synthesis of VHDL codes using Quartus Integrated Synthesis (QIS) tools was performed by implementing Altera's library (90-nm) to make the synthesized design downloaded to a Field Programmable Gate Array (FPGA) board. The synthesis software was also used to optimize the performance of the design related features such as chip area, delay, clock frequency and power dissipation. The book presents the development of fast processor in a lucid fashion so that the readers would grasp the theme presented, and be motivated to actually realize the developed processor as well as implement the ideas in their own designs.

Data Compression: Lossless Data Compression, Lossy Compression, Image Compression, White Noise, Video Compression, Prefix Code

Purchase includes free access to book updates online and a free trial membership in the publisher's book club where you can select from more than a million books without charge. Chapters: Lossless Data Compression, Lossy Compression, Image Compression, White Noise, Video Compression, Prefix Code, Data Compression Ratio, Data Compaction, Winzip, Bitstream Format, Audio Compression, Error Exponent, Shannon's Source Coding Theorem, Rate-distortion Theory, Progressive Graphics File, Drivespace, Binary Ordered Compression for Unicode, Compression Artifact, Universal Code, Ocarina Networks, Generation Loss, Bitrate Peeling, Sardinas-patterson Algorithm, Dictionary Coder, Four-Stage Model of Data Compression, Rohc, Move-To-Front Transform, Sub-Band Coding, Hutter Prize, Leb128, Transparency, Lzx, Double Tools for Doublespace, Smart Bitrate Control, Adaptive Coding, Zeosync, Solid Compression, Libsigcomp, Unary Coding, Modulo-N Code, Self-Extracting Archive, Lossy Data Conversion, Cmx, Zoo, Grammar-Based Code, Universal Data Compression, Signaling Compression, Jan Sloot, Recursive Indexing, Data Compression Symmetry, Compressed Pattern Matching, Trellis Quantization, Van Jacobson Tcp/ip Header Compression, Precompressor, Qdx, Ultra Low Delay Audio Coder, Krichevsky-trofimov Estimator, Calgary Corpus, Set Partitioning in Hierarchical Trees, Volume, Context Mixing, Silence Compression, Transparency Threshold, Canterbury Corpus, Twin Vector Quantization. Excerpt: Lossless data compression is a class of data compression algorithms that allows the exact original data to be reconstructed from the compressed data. The term lossless is in contrast to lossy data compression, which only allows an approximation of the original data to be reconstructed, in exchange for better compression rates. Lossless data compression is used in many applications. For example, it is used in the popular ZIP file format and in the Unix tool gzip. It is also often... More: http://booksllc.net/?id=18209

Image Processing: Color, Convolution, Image Compression, List of Fourier-Related Transforms, Charge-Coupled Device, Pixel

Purchase includes free access to book updates online and a free trial membership in the publisher's book club where you can select from more than a million books without charge. Chapters: Color, Convolution, Image Compression, List of Fourier-Related Transforms, Charge-Coupled Device, Pixel, Digital Image Processing, Anti-Aliasing, Jaggies, Binary Image, Framebuffer, Angle of View, Digital Image, Harris Affine Region Detector, Color Vision, Corner Detection, Scale Space, Segmentation, Medical Imaging, Ridge Detection, Scene Statistics, Kadir Brady Saliency Detector, Mathematical Morphology, Edge Detection, Image Editing, Color Balance, Pixel Aspect Ratio, Scale Space Implementation, Hough Transform, Structure Tensor, Noise Reduction, Blob Detection, Geo Warping, Histogram Equalization, Nearest Neighbor Search, Feature Detection, Color Quantization, Color Space, Deconvolution, Network Abstraction Layer, Canny Edge Detector, Multiple Buffering, Sobel Operator, Gaussian Blur, Topological Skeleton, Bicubic Interpolation, Chirplet Transform, Region Growing, Photoanalysis, Hessian Affine Region Detector, Image Resolution, Pixel Art Scaling Algorithms, Imagej, Progressive Graphics File, Anisotropic Diffusion, Blend Modes, Template Matching, Affine Shape Adaptation, Feature, Masking, Opponent Process, Unsharp Masking, Multiple Satellite Imaging, Intrinsic Dimension, Scale-Space Segmentation, Thresholding, Microscope Image Processing, Level Set Method, Computational Photography, Modulation Transfer Function, Lenna, Socet Set, Error Diffusion, List of Image Analysis Software, Difference of Gaussians, Foveated Imaging, Circular Convolution, Signal to Noise Ratio, Super-Resolution, Abel Transform, Wiener Deconvolution, Teleradiology, Focus Recovery Based on the Linear Canonical Transform, Principal Curvature-Based Region Detector, Hankel Transform, Gemident, Erosion, Scale-Space Axioms, Complex Wavelet Transform, Hdr Photostudio, Image Stitching, Block Truncation Coding, Sha...

AUTOENCODER NEURAL NETWORKS: A Performance Study Based on Image Reconstruction, Recognition and Compression

Autoencoders are feedforward neural networks which can have more than one hidden layer. These networks attempt to reconstruct the input data at the output layer. Since the size of the hidden layer in the autoencoders is smaller than the size of the input data, the dimensionality of input data is reduced to a smaller-dimensional code space at the hidden layer. However, training a multilayer autoencoder is tedious. This is due to the fact that the weights at deep hidden layers are hardly optimized. The research work has focused on the characteristics, training and performance evaluation of autoencoders. The concepts of stacking and Restricted Boltzmann Machine have also been discussed in detail. Two datasets, namely ORL face dataset and MNIST handwritten digit dataset have been employed in these experiments. The performances of the autoencoders have also been compared with that of PCA. It has been shown that the autoencoders can also be used for image compression. The compression efficiency has been studied using DDSM dataset (mammogram dataset). Since image patches were used for training, it was possible to compress and decompress mammograms of different sizes.

Compression File Systems: Ntfs, Zfs, Apple Disk Image, Jffs2, Squashfs, Cloop, Cramfs, Zfs+, Axfs

Purchase includes free access to book updates online and a free trial membership in the publisher's book club where you can select from more than a million books without charge. Chapters: Ntfs, Zfs, Apple Disk Image, Jffs2, Squashfs, Cloop, Cramfs, Zfs+, Axfs, E2compr. Excerpt: AXFS (Advanced XIP Filesystem) is a compressed read-only file system for Linux . Designed to utilize XIP alongside compression to reduce boot and load times whilst retaining a small footprint for embedded devices . AXFS is free software (licensed under the GPL ). See also (online edition) Websites (URLs online) A hyperlinked version of this chapter is at Filename extension : .dmg A file with the extension .dmg uses a proprietary disk image format commonly found on Mac OS X . The format allows secure password protection as well as file compression and hence serves both security and file distribution functions. Its most common function is the distribution of software over the Internet. When opened, DMG files are "mounted " as a drive within the Finder . DMG files can be easily created (with or without encryption ) using utilities that are included in OS X: Disk Utility in Mac OS X v10.3 and newer versions, or Disk Copy in Mac OS X v10.2 and earlier versions. These utilities also use DMG files as images for burning CDs and DVDs. DMG files may also be managed via the command line using the hdiutil utility. DMG files are published with a MIME type of application/x-apple-diskimage . As many web server administrators tend to be less knowledgeable about Apple-specific file types, this MIME type is often not set, resulting in the user experience of attempting to download DMG files as text directly to the browser window, forcing the use of a control-click or similar workaround to download the file. For this reason, DMG files may be distributed as bzip2 (.dmg.bz2) or ZIP (.dmg.zip) files. These wrappers typically don't compress the file further, but rather help ensure that the files are handled corr...

Pages: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34

Search more books