Search results for "Texture compression"

showing 7 items of 7 documents

Complex networks : application for texture characterization and classification

2008

This article describes a new method and approch of texture characterization. Using complex network representation of an image, classical and derived (hierarchical) measurements, we presente how to have good performance in texture classification. Image is represented by a complex networks : one pixel as a node. Node degree and clustering coefficient, using with traditionnal and extended hierarchical measurements, are used to characterize ”organisation” of textures.

Computer engineering. Computer hardwareTexture compressionComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONComplex networksImage processingTexture (geology)TK7885-7895Image textureImage processingAnàlisi de texturaProcesamiento de imágenestexture analysisClustering coefficientAnálisis de texturaRedes complejasPixelbusiness.industryNode (networking)Pattern recognitionProcessament d'imatgescomplex networksQA75.5-76.95Xarxes complexesComplex networkTexture analysisElectronic computers. Computer scienceComputer Science::Computer Vision and Pattern RecognitionComputer Vision and Pattern RecognitionArtificial intelligencebusinessSoftwareELCVIA: electronic letters on computer vision and image analysis
researchProduct

Comparative study of multi-2D, Full 3D and hybrid strategies for multi/hyperspectral image compression

2009

In this paper, we investigate appropriate strategies for multi/hyperspectral image compression. In particular, we compare the classic multi-2D compression strategy and two different implementations of 3D strategies (Full 3D and hybrid). All strategies are combined with a PCA decorrelation stage to optimize performance. For multi-2D and hybrid strategies, we propose a weighted version of PCA. Finally, for consistent evaluation, we propose a larger comparison framework than the conventionally used PSNR. The results are significant and show the weaknesses and strengths of each strategy.

Image codingTexture compressionbusiness.industryCompression (functional analysis)Hyperspectral image compressionPrincipal component analysisPattern recognitionArtificial intelligencebusinessDecorrelationMathematicsData compression2009 Proceedings of 6th International Symposium on Image and Signal Processing and Analysis
researchProduct

Efficient image compression using directionlets

2007

Directionlets are built as basis functions of critically sampled perfect-reconstruction transforms with directional vanishing moments imposed along different directions. We combine the directionlets with the space-frequency quantization (SFQ) image compression method, originally based on the standard two-dimensional wavelet transform. We show that our new compression method outperforms the standard SFQ as well as the state-of-the-art image compression methods, such as SPIHT and JPEG-2000, in terms of the quality of compressed images, especially in a low-rate compression regime. We also show that the order of computational complexity remains the same, as compared to the complexity of the sta…

Lossless compressionTexture compressionbusiness.industryWavelet transformSet partitioning in hierarchical treesWaveletComputer visionArtificial intelligencebusinessQuantization (image processing)AlgorithmMathematicsData compressionImage compression2007 6th International Conference on Information, Communications & Signal Processing
researchProduct

Image compression based on a multi-directional map-dependent algorithm

2007

Abstract This work is devoted to the construction of a new multi-directional edge-adapted compression algorithm for images. It is based on a multi-scale transform that is performed in two steps: a detection step producing a map of edges and a prediction/multi-resolution step which takes into account the information given by the map. A short analysis of the multi-scale transform is performed and an estimate of the error associated to the largest coefficients for a piecewise regular function with Lipschitz edges is provided. Comparisons between this map-dependent algorithm and different classical algorithms are given.

Lossless compressionWork (thermodynamics)Texture compressionApplied MathematicsPiecewiseFunction (mathematics)Lipschitz continuityAlgorithmMathematicsImage compressionData compressionApplied and Computational Harmonic Analysis
researchProduct

Copy-move Forgery Detection via Texture Description

2010

Copy-move forgery is one of the most common type of tampering in digital images. Copy-moves are parts of the image that are copied and pasted onto another part of the same image. Detection methods in general use block-matching methods, which first divide the image into overlapping blocks and then extract features from each block, assuming similar blocks will yield similar features. In this paper we present a block-based approach which exploits texture as feature to be extracted from blocks. Our goal is to study if texture is well suited for the specific application, and to compare performance of several texture descriptors. Tests have been made on both uncompressed and JPEG compressed image…

Texture compressionComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage forensicscomputer.file_formatTexture (music)JPEGUncompressed videoDigital imageImage textureBlock (programming)Feature (computer vision)Computer visionArtificial intelligencebusinesscomputer
researchProduct

New techniques for visualization of losses due to image compression in grayscale medical still images

2003

To evaluate the visual influence of irreversible compression on medical images, changes of the images have to be visualized. The authors have explored alternative techniques to be used instead of the usual side-by-side comparison, where the information contained in both images is perceived in a single image, preserving the context between compression errors and image structures. Thus fast and easy comparison can be done. These techniques make use of the human ability to perceive information also in the dimensions of color, space, and time. A study was performed with JPEG-compressed coronary angiographic images. Changes in the resulting images for six compression factors from 7 to 30 were sc…

Texture compressionStandard test imagebusiness.industryComputer scienceImage processingcomputer.file_formatLossy compressionJPEGComputer visionArtificial intelligenceQuantization (image processing)businesscomputerImage compressionData compressionProceedings Computers in Cardiology
researchProduct

Mesh connectivity compression using convection reconstruction

2007

International audience; During a highly productive period running from 1995 to about 2002, the research in lossless compression of 3D meshes mainly consisted in a hard battle for the best bitrates. But for a few years, compression rates seem stabilized around 1.5 bit per vertex for the connectivity coding of usual meshes, and more and more work is dedicated to remeshing, lossy compression, or gigantic mesh compression, where memory and CPU optimizations are the new priority. However, the size of 3D models keeps growing, and many application fields keep requiring lossless compression. In this paper, we present a new contribution for single-rate lossless connectivity compression, which first …

Theoretical computer scienceTexture compressionLossless[ MATH.MATH-IT ] Mathematics [math]/Information Theory [math.IT]02 engineering and technologyLossy compression[INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG][MATH.MATH-IT] Mathematics [math]/Information Theory [math.IT][ INFO.INFO-IT ] Computer Science [cs]/Information Theory [cs.IT]I.3.5 [Computing Methodologies]: Computer Graphics--Computational Geometry and Object Modeling0202 electrical engineering electronic engineering information engineeringPolygon meshComputingMethodologies_COMPUTERGRAPHICSMathematicsMeshConnected componentLossless compressionConnectivityDelaunay triangulationCompression[MATH.MATH-IT]Mathematics [math]/Information Theory [math.IT]020207 software engineering[INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG][INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT][ INFO.INFO-CG ] Computer Science [cs]/Computational Geometry [cs.CG]020201 artificial intelligence & image processing[INFO.INFO-IT] Computer Science [cs]/Information Theory [cs.IT]ReconstructionAlgorithmImage compressionData compressionProceedings of the 2007 ACM symposium on Solid and physical modeling
researchProduct