A chip set for lossless image compression

The authors describe two chips which form the basis of a high-speed lossless image compression/decompression system. They present the transform and coding algorithms and the main architectural features of the chips and outline some performance specifications. Lossless compression can be achieved by a transformation process followed by entropy coding. The two application-specific integrated circuits (ASICs) perform S-transform image decomposition and the Lempel-Ziv (L-Z) type of entropy coding. The S-transform, besides decorrelating the image, provides a convenient method of hierarchical image decomposition. The data compressor/decompressor IC is a fast and efficient implementation of the L-Z algorithm. The chips can be used independently or together for image compression     

A set of transformations for lossless image compression

Based on the property of binary arithmetic operations and the spatial probability distribution of the prediction error, a set of transformations is proposed for the lossless image compression. The bit plane coding technique is used in the transformed image. The transformations are easily implementable. Experimental results show that these transformations are useful.     

SIXTEEN TREE METHOD FOR BILEVEL IMAGE DATA COMPRESSION

A sixteen tree method of data compression of bilevel image is described.Thismethod has high efficiency,no information loss during compression,and easy to realize.     

Image registration for image-based rendering.

Image-based rendering (IBR) has received much attention in recent years for its ability to synthesize photo-realistic novel views. To support translational motion, existing IBR methods either require a large amount of reference images or assume that some geometric information is available. However, rendering with a large amount of images is very expensive in terms of image acquisition, data storage, and memory costs. As IBR accepts various kinds of geometric proxy, we may use image registration techniques, such as stereo matching and structure and motion recognition, to obtain geometric information to help reduce the number of images required. Unfortunately, existing image registration techniques only support a small search range and require closely sampled reference images. This results in a high spatial sampling rate, making IBR impractical for use in scalable walkthrough environments.Our primary objective of this project is to develop an image registration technique that would recover the geometric proxy for IBR while, at the same time, reducing the number of reference images required. In this paper, we analyze the roles and requirements of an image registration technique for reducing the spatial sampling rate. Based on these requirements, we present a novel image registration technique to automatically recover the geometric proxy from reference images. With the distinguishing feature of supporting a large search range, the new method can accurately identify correspondences even though the reference images may only be sparsely sampled. This can significantly reduce the acquisition effort, the model size, and the memory cost.     

An RBF-based compression method for image-based relighting.

In image-based relighting, a pixel is associated with a number of sampled radiance values. This paper presents a two-level compression method. In the first level, the plenoptic property of a pixel is approximated by a spherical radial basis function (SRBF) network. That means that the spherical plenoptic function of each pixel is represented by a number of SRBF weights. In the second level, we apply a wavelet-based method to compress these SRBF weights. To reduce the visual artifact due to quantization noise, we develop a constrained method for estimating the SRBF weights. Our proposed approach is superior to JPEG, JPEG2000, and MPEG. Compared with the spherical harmonics approach, our approach has a lower complexity, while the visual quality is comparable. The real-time rendering method for our SRBF representation is also discussed.     

Geometry-assisted image-based rendering for facial analysis and synthesis

In this paper, we present an image-based method for the tracking and rendering of faces. We use the algorithm in an immersive video conferencing system where multiple participants are placed in a common virtual room. This requires viewpoint modification of dynamic objects. Since hair and uncovered areas are difficult to model by pure 3-D geometry-based warping, we add image-based rendering techniques to the system. By interpolating novel views from a 3-D image volume, natural looking results can be achieved. The image-based component is embedded into a geometry-based approach in order to limit the number of images that have to be stored initially for interpolation. Also temporally changing facial features are warped using the approximate geometry information. Both geometry and image cube data are jointly exploited in facial expression analysis and synthesis.     

Precision isosurface rendering of 3D image data

We address the task of rendering by ray tracing the isosurface of a high-quality continuous model of volumetric discrete and regular data. Based on first principles, we identify the quadratic B-spline as the best model for our purpose. The nonnegativity of this basis function allows us to confine the potential location of the isosurface within a binary shell. We then show how to use the space-embedding property of splines to further shrink this shell to essentially a single voxel width. Not all rays traced through a given shell voxel intersect the isosurface; many may only graze it, especially when the ray-tracing vantage point is close to or within the volume to be rendered. We propose an efficient heuristic to detect those cases. We present experiments to support our claims.     

SAR image data compression using a tree-structured wavelettransform

SAR image compression is very important in reducing the costs of data storage and transmission in relatively slow channels. The authors propose a compression scheme driven by texture analysis, homogeneity mapping and speckle noise reduction within the wavelet framework. The image compressibility and interpretability are improved by incorporating speckle reduction into the compression scheme. The authors begin with the classical set partitioning in hierarchical trees (SPIHT) wavelet compression scheme, and modify it to control the amount of speckle reduction, applying different encoding schemes to homogeneous and nonhomogeneous areas of the scene. The results compare favorably with the conventional SPIHT wavelet and the JPEG compression methods     

A segmentation-based lossless image coding method forhigh-resolution medical image compression

Lossless compression techniques are essential in archival and communication of medical images. Here, a new segmentation-based lossless image coding (SLIC) method is proposed, which is based on a simple but efficient region growing procedure. The embedded region growing procedure produces an adaptive scanning pattern for the image with the help of a very-few-bits-needed discontinuity index map. Along with this scanning pattern, an error image data part with a very small dynamic range is generated. Both the error image data and the discontinuity index map data parts are then encoded by the Joint Bi-level Image Experts Group (JBIG) method. The SLIC method resulted in, on the average, lossless compression to about 1.6 b/pixel from 8 b, and to about 2.9 b/pixel from 10 b with a database of ten high-resolution digitized chest and breast images. In comparison with direct coding by JBIG, Joint Photographic Experts Group (JPEG), hierarchical interpolation (HINT), and two-dimensional Burg prediction plus Huffman error coding methods, the SLIC method performed better by 4% to 28% on the database used     

A method of block truncation coding for color image compression

A basic color block truncation coding (CBTC) algorithm for color image compression is described. A modification of the algorithm that reduces truncation errors is also described. The block statistics related to CBTC methods are investigated. Some experimental results are given for a 256-×256-pixel color image with 24 b/pixel     

Efficient interpolation scheme for image sequence data compression

Presents a video coding approach that requires a very low bit rate and achieves good visual quality. The approach allows easy and cheap hardware implementation. Intra- and interframe correlations are fully exploited through a spatio-temporal interpolation applied to a nonuniform 3D grid     

An image compression method for spatial search

The maintenance of large raster images under spatial operations is still a major performance bottleneck. For reasons of storage space, images in a collection, such as satellite pictures in geographic information systems, are maintained in compressed form. Instead of performing a spatially selective operation on an image by first decompressing the compressed version, we propose to perform queries directly on the compressed version of the image. We suggest a compression technique that allows for the subsequent use of a spatial index structure to guide a spatial search. In response to a window query, our algorithm delivers a compressed partial image, or the exact uncompressed requested image region. In addition to the support of spatial queries on compressed continuous tone images, the new compression algorithm is even competitive in terms of the compression ratio that it achieves, compared to other standard lossless compression techniques.     

Progressive decoding method for fractal image compression

Fractal image compression is an efficient technique for compactly coding images, in which an image is encoded by a contractive transformation whose fixed point is close to the original image, and then is decoded by using an iteration procedure stemmed from the well known Banach fixed-point theorem. A new fixed-point iteration theorem with a control parameter is presented, which provides a novel iteration procedure that progressively approaches the fixed point of a contractive transformation and particularly reverts back to the conventional iteration procedure when the control parameter is set as one. Based on the new iteration procedure, a progressive decoding algorithm is proposed for fractal image compression, which does not need any specific fractal encoder and is useful for low bandwidth transmission. The experimental results demonstrate that the progressive fractal decoding is capable of controlling the decoding iteration procedure by varying the control parameter values and displaying progressively how the original image is obtained from a black image or another image at each step of the increasing iterations.     

A new LBG-based image compression method using DCT

In this letter, a new Linde-Buzo-Gray （LBG）-based image compression method using Discrete Cosine Transform （DCT） and Vector Quantization （VQ） is proposed. A gray-level image is firstly decomposed into blocks, then each block is subsequently encoded by a 2D DCT coding scheme. The dimension of vectors as the input of a generalized VQ scheme is reduced. The time of encoding by a generalized VQ is reduced with the introduction of DCT process. The experimental results demonstrate the efficiency of the proposed method.     

Motion differential set partition coding for image sequence and video compression

Efficient image sequence coding exploits both intra- and inter-frame correlations. Set partition coding (SPC) is efficient in intra-frame de-correlation for still images. Based on SPC, a novel image sequence coding system, called motion differential SPC (M-D-SPC), is presented in this paper. It removes inter-frame redundancy by re-using the significance map of a previously SPC coded frame. Every frame is encoded and decoded separate from other frames. Furthermore, there is no reconstruction of encoded frames in the encoder, as is done with interframe prediction methods. The M-D-SPC exhibits an auxiliary key frame coding framework, which achieves higher coding efficiency compared to the all-intra-coding schemes and meanwhile maintains the beneficial features of SPC all-intra-coding, such as computational simplicity, rate scalability, error non-propagation, and random frame access. SPIHT-based simulations on hyperspectral images, 3D/4D medical images, and video show greater compression efficiency than the standard intraframe coding method of motion JPEG2000.     

Lossless compression of multispectral image data

While spatial correlations are adequately exploited by standard lossless image compression techniques, little success has been attained in exploiting spectral correlations when dealing with multispectral image data. The authors present some new lossless image compression techniques that capture spectral correlations as well as spatial correlation in a simple and elegant manner. The schemes are based on the notion of a prediction tree, which defines a noncausal prediction model for an image. The authors present a backward adaptive technique and a forward adaptive technique. They then give a computationally efficient way of approximating the backward adaptive technique. The approximation gives good results and is extremely easy to compute. Simulation results show that for high spectral resolution images, significant savings can be made by using spectral correlations in addition to spatial correlations. Furthermore, the increase in complexity incurred in order to make these gains is minimal     

An efficient depth image-based rendering with depth reliability maps for view synthesis

In this paper, an efficient depth image-based rending (DIBR) with depth reliability maps (DRM) is proposed to improve the quality of synthesized images. First, a DRM-based occlusion-aware approach is developed to obtain a segmentation mask, which can explicitly indicate where the information in an intermediate image should be blended preferably. Next, an improved weight model for view creation is introduced to enhance the quality of synthesized images. Finally, a distance and depth-based sub-pixel weighted (DDSPW) algorithm is presented to solve the visibility and resampling problems. Experimental results demonstrate that the treated DIBR schemes have better performance for view synthesis than the other three methods through the subjective visual perception and objective assessments in terms of peak signal to noise ratio and structural similarity index.     

超光谱图像数据压缩方法综述

针对目前超光谱图像的编码压缩还没有一个公认的标准或已成熟的压缩方法，本文对主要的几类超光谱图像压缩方法进行了介绍，并给出了各类压缩方法无损压缩的压缩比。随着对超光谱图像压缩研究的深入，多种方法结合使用的趋势愈加明显。通过对各种超光谱压缩技术的分析比较，为超光谱压缩算法的研究奠定了良好基础。