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检索条件"任意字段=Mathematics of Data/Image Coding. Compression, and Encryption"

共 163 条记录，以下是131-140 订阅

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Fast classification method for fractal image compression

Fast classification method for fractal image compression

引用

Conference on mathematics and Applications of data/image coding. compression, and encryption III

作者： Truong, TK Jeng, JH I Shou Univ Coll Elect & Informat Engn Kaohsiung Taiwan

ISBN: (纸本)0819437670

In this paper, a fast algorithm is developed which reduces the searching space for Fractal image coding. The basic idea is to classify the domain pool into three classes, non-edged class, horizontal/vertical class and the diagonal class. For each given range block the property is computed first to determine which class it belongs. Then one only has to search from the corresponding class in the domain pool to find the best match. The classification operation is performed only according to the lowest frequency coefficients of the given block in the horizontal and vertical directions, in which the frequency data is computed from Discrete Cosine Transform (DCT). There main advantages for this classification scheme are that the classification mechanism is simple and the DCT algorithm is easy to implement. A simulation shows that, the proposed fast algorithm is about 2 times faster than the baseline method while the quality of the retrieved image is almost the same.

关键词： fractal image compression self-similarity classification DCT

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Implementation IDEA algorithm for image encryption

Implementation IDEA algorithm for image encryption

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Conference on mathematics and Applications of data/image coding. compression, and encryption III

作者： Dang, PP Chau, PM Univ Calif San Diego Dept Elect & Comp Engn La Jolla CA 92093 USA

ISBN: (纸本)0819437670

In this paper, we present an implementation of the IDEA algorithm for image encryption. The image encryption is incorporated into the compression algorithm for transmission over a data network, in the proposed method, Embedded Wavelet Zero-tree coding.is used for image compression. Experimental results show that our proposed scheme enhances data security and reduces the network bandwidth required for video transmissions. A software implementation and system architecture for hardware implementation of the IDEA image encryption algorithm based on Field Programmable Gate Array (FPGA) technology are presented in this paper.

关键词： image encryption encryption decryption IDEA FPGA reconfigurable processor

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Quality issues for archival of ancient documents

Quality issues for archival of ancient documents

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Conference on mathematics and Applications of data/image coding. compression, and encryption III

作者： Aiazzi, B Baronti, S Casini, A Lotti, F Mattei, A Santurri, L CNR IROE Nello Carrara Res Inst Electromagnet Waves I-50127 Florence Italy

ISBN: (纸本)0819437670

This paper reports about a study concerning the application of error bounded encoding.to lossy image compression of ancient documents handwritten on parchments. images are acquired in the RGB color space and previously transformed in the YUV color coordinate system before coding. The coding.algorithm, named RLP, considered here is based on a classified DPCM enhanced by a fuzzy clustering initialization and followed by context based statistical modeling and arithmetic coding.of prediction residuals that are quantized with user defined odd step sizes to allow rate control with a minimum peak error over the whole image, so as to exactly limit local distortions. Each YUV component is coded separately;after decoding.images are transformed back to RGB color space and compared with the originals in order to quantify distortions. A relationship bounding the peak errors in the RGB color space once the peak error is fixed in the YUV color space is derived. An algorithm originally designed for estimating signal-dependent noise parameters and used to obtain useful information about the images of the documents is also reported in the paper. The performances of the coding.method are superior with respect to conventional DPCM schemes thanks to its flexibility and robustness to changes in type of images. For the compression ratios requested by this application the gain of RLP over JPEG is consistent: nearly 2 dB and 5 dB in PSNR for compression ratios of 10 and 5 respectively.

关键词： near Lossless compression error bounding encoding cultural heritage archival parchments acquisition film-grain noise signal-dependent noise noise estimation

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Near-lossless image compression: a key to high-quality data distribution

Near-lossless image compression: a key to high-quality data ...

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Conference on mathematics and Applications of data/image coding. compression, and encryption III

作者： Aiazzi, B Alparone, L Baronti, S CNR IROE Nello Carrara Res Inst Electromagnet Waves I-50127 Florence Italy

ISBN: (纸本)0819437670

This paper promotes the use of near-lossless image compression and describes two DPCM schemes suitable for this purpose. The former is causal and is based on a classified linear-regression prediction followed by context-based arithmetic coding.of the outcome residuals. It provides impressive performances, both with and without loss, especially on medical images. coding.time are affordable thanks to fast convergence of training. Decoding.is always performed in realtime. The latter is a noncausal DPCM and relies on a modified Laplacian pyramid in which feedback of quantization errors is introduced in order to upper bound reconstruction errors. Although the predictive method is superior for medium and high rates, the pyramid encoder wins for low rates and allows to encode and decode both in realtime. Comparisons with block-DCT JPEG show that the proposed schemes are more than competitive also in terms of rate distortion.

关键词： classified DPCM interpolative DPCM enhanced Laplacian pyramid medical images near-lossless compression quantization noise feedback relaxation labeling remote sensing images statistical context modeling

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Decimation vs. quantization for data compression in TDOA systems

Decimation vs. quantization for data compression in TDOA sys...

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Conference on mathematics and Applications of data/image coding. compression, and encryption III

作者： Fowler, ML SUNY Binghamton Dept Elect Engn Binghamton NY 13901 USA

ISBN: (纸本)0819437670

The location of an electromagnetic emitter is commonly estimated by intercepting its signal and then sharing the data among several platforms. Doing this in a timely fashion requires effective data compression. Previous data compression efforts have focused on minimizing the mean-square error (MSE) due to compression. However, this criterion is likely to fall short because it fails to exploit how the signal's structure impacts the parameter estimates. Because TDOA accuracy depends an the signal's RMS bandwidth, compression techniques that can significantly reduce the amount of data while negligibly impacting the RIMS bandwidth have great potential. We show that it is possible to exploit this idea by balancing the impacts of simple filtering/decimation and quantization and derive a criterion that determines an optimal balance between the amount of decimation and the level of quantization. This criterion is then used to show that by using a combination of decimation and quantization it is possible to meet requirements on data transfer time that can't be met through quantization alone. Furthermore, when quantization-alone approaches can meet the data transfer time requirement, we demonstrate that the decimation/quantization approach can lead to better TDOA accuracies. Rate-distortion curves are plotted to show the effectiveness of the approach.

关键词： data compression emitter location time-difference-of-arrival TDOA quantization decimation

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Power- and space-efficient image computation with compressive processing. 1. Background and theory

Power- and space-efficient image computation with compressiv...

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Conference on mathematics and Applications of data/image coding. compression, and encryption III

作者： Schmalz, MS Univ Florida Dept Comp & Informat Sci & Engn Gainesville FL 32611 USA

ISBN: (纸本)0819437670

Surveillance imaging applications on small autonomous imaging platforms present challenges of highly constrained power supply and form factor, with potentially demanding specifications for target detection and recognition. Absent of significant advances in image processing hardware, such power and space restrictions can imply severely limited computational capabilities. This holds especially for compute-intensive algorithms with high-precision fixed- or floating-point operations in deep pipelines that process large data streams. Such algorithms tend not to be amenable to small or simplified architectures involving (for example) reduced precision, reconfigurable logic, low-power gates, or energy recycling schemes. In this series of two papers, a technique of reduced-power computing called compressive processing (CXP) is presented and applied to several low- and mid-level computer vision operations. CXP computes over compressed data without resorting to intermediate decompression steps. As a result of fewer data due to compression, fewer operations are required by CXP than are required by computing over the corresponding uncompressed image. In several cases, CXP techniques yield speedups on the order of the compression ratio. Where lossy high-compression transforms are employed, it is often possible to use approximations to derive CXP operations to yield increased computational efficiency via a simplified mix of operations. The reduced work requirement, which follows directly from the presence of fewer data, also implies a reduced power requirement, especially if simpler operations are involved in compressive versus noncompressive operations. Several image processing algorithms (edge detection, morphological operations, and component labelling) are analyzed in the context of three compression transforms: vector quantization (VQ), visual pattern image coding.(VPIC), and EBLAST. The latter is a lossy high-compression transformation developed for underwater communication

关键词： image compression error analysis compressive processing

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EBLAST - efficient, high-compression image transformation. 2. Implementation and results

EBLAST - efficient, high-compression image transformation. 2...

引用

Conference on mathematics and Applications of data/image coding. compression, and encryption III

作者： Schmalz, MS Ritter, GX Caimi, FM Univ Florida Dept Comp & Informat Sci & Engn Gainesville FL 32611 USA

ISBN: (纸本)0819437670

The efficient computation of high-compression encoding.transforms is key to transmission of moderate- or high-resolution imagery along low- to moderate-bandwidth channels. Previous approaches to image compression have employed low-compression transforms for lossless encoding. as well as moderate compression for archival storage. Such algorithms are usually block-structured and thus tend to be amenable to computation on array processors, particularly embedded SIMD meshes. These architectures are important for fast processing of imagery obtained from airborne or underwater surveillance platforms, particularly in the case of underwater autonomous vehicles, which tend to be severely power-limited. Recent research in high-compression image encoding.has yielded a variety of hierarchically structured transforms such as EPIC, SPIHT, or wavelet based compression algorithms, which unfortunately do not map efficiently to embedded parallel processors with small memory models. In response to this situation, the EBLAST transform was developed to facilitate transmission of underwater imagery along noisy, low-bandwidth acoustic communication channels. In this second part of a two-part series [1] is presented implementational issues and experimental results from the application of EBLAST to a database of underwater imagery, as well as to common reference images such as lena, baboon, etc. It is shown that the range of EBLAST compression ratios (100:1 < CR < 250:1) can be maintained with mean-squared-error (MSE) less than five percent of full greyscale range, with computational efficiency that facilitates video-rate compression with existing off-the-shelf technology at frame sizes of 512x512 pixels or less. Additional discussion pertains to postprocessing steps that can render an EBLAST-decompressed image more realistic visually, in support of human target cueing.

关键词： image compression parallel computing

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Content-dependent, frame-selective video compression

Content-dependent, frame-selective video compression

引用

Conference on mathematics and Applications of data/image coding. compression, and encryption III

作者： Power, GJ USAF Res Lab Wright Patterson AFB OH 45433 USA

ISBN: (纸本)0819437670

The transmission and storage of digital video currently requires more bandwidth than is typically available. Emerging applications such as video-on-demand, web cameras, and collaborative tools with video conferencing are pushing the limits of the transmission media to provide video to the desktop computer. Lossy compression has succeeded in meeting some of the video demand, but it suffers from artifacts and low resolution. This paper introduces a content-dependent, frame-selective compression technique which is developed wholly as a preconditioner that can be used with existing digital video compression techniques. The technique is heavily dependent on a priori knowledge of the general content of the video which uses content knowledge to make smart decisions concerning the frames selected for storage or transmission. The velocital information feature of each frame is calculated to determine the frames with the most active changes. The velocital information feature along with a priori knowledge of the application allows prioritization of the frames. Frames are assigned priority values with the higher priority frames being selected for transmission based on available bandwidth. The technique is demonstrated for two applications: an airborne surveillance application and a worldwide web camera application. The airborne surveillance application acquires digital infrared video of targets at a standard frame rate of 30 frames per second, but the imagery suffers from infrared sensor artifacts and spurious noise. The web camera application selects frames at a slow rate but suffers from artifacts due to lighting and reflections. The results of using content-dependent, frame-selective video compression shows improvement in image quality along with reduced transmission bandwidth requirements.

关键词： video compression velocital information feature data storage and retrieval video transmission motion imagery image sequence analysis

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Space, time, error, and power optimization of image compression transforms

Space, time, error, and power optimization of image compress...

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Conference on mathematics and Applications of data/image coding. compression, and encryption III

作者： Schmalz, MS Ritter, GX Caimi, FM Univ Florida Dept Comp & Informat Sci & Engn Gainesville FL 32611 USA

ISBN: (纸本)0819437670

The implementation of an image compression transform on one or more small, embedded processors typically involves stringent constraints on power consumption and form factor. Traditional methods of optimizing compression algorithm performance typically emphasize joint minimization of space and time complexity, often without significant consideration of arithmetic accuracy or power consumption. However, small autonomous imaging platforms typically require joint optimization of space, time, error (or accuracy), and power (STEP) parameters, which the authors call STEP optimization. In response to implementational constraints on space and power consumption, the authors have developed systems and techniques for STEP optimization that are based on recent research in VLSI circuit design, as well as extensive previous work in system optimization. Building on the authors' previous research in embedded processors as well as adaptive or reconfigurable computing, it is possible to produce system-independent STEP optimization that can be customized for a given set of system-specific constraints. This approach is particularly useful when algorithms for image and signal processing (ISP) computer vision (CV), or automated target recognition (ATR), expressed in a machine-independent notation, are mapped to one or more heterogeneous processors (e.g., digital signal processors or DSPs, SIMD mesh processors, or reconfigurable logic). Following a theoretical summary, this paper illustrates various STEP optimization techniques via case studies, for example, real-time compression of underwater imagery on board an autonomous vehicle. Optimization algorithms are taken from the literature, and error profiling/analysis methodologies developed in the authors' previous research are employed. This yields a more rigorous basis for the simulation and evaluation of compression algorithms on a wide variety of hardware models. In this study, image algebra is employed as the notation of choice. Develop

关键词： image compression error analysis performance simulation

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Analysis of error in measuring laryngeal size parameters from compressed imagery

Analysis of error in measuring laryngeal size parameters fro...

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Conference on mathematics and Applications of data/image coding. compression, and encryption III

作者： Sapienza, C Al-Natour, Y Schmalz, MS Ritter, GX Univ Florida Dept Commun Sci & Disorders Gainesville FL 32611 USA

ISBN: (纸本)0819437670

The accurate, consistent measurement of laryngeal size parameters is key to the quantification of phonatory disorders from laryngeal endoscopic imagery. Unfortunately, laryngoscopic images contain a wide variety of distortions introduced by endoscope optics (e.g., barrel distortion), systematic effects such as mucus strands adhering to the endoscope lens, electronic noise in the camera or digitization hardware, and color distortions resulting from optical, camera, or digitization errors. These difficulties are compounded by representational errors introduced during image archival or telemedicine-based manipulation of endoscopic imagery, e.g., when images are compressed, stored, then decompressed using lossy transformations. A variety of researchers, in particular Omori et al. [1], have studied the measurement of laryngeal parameters from a variety of image sources. Unfortunately, such analyses do not account for the effects of image compression/decompression. In this paper, previous research is extended to include estimation of errors in the measurement of parameters such as glottal gap area and maximum vocal fold length from compressed laryngoscopic imagery. compression transforms studied include JPEG [2] and EBLAST [3], a relatively recent development in high-compression image transformation for communication along low-bandwidth channels. Error analysis emphasizes preservation of spatial and greylevel information in the decompressed imagery, as well as error in parameter measurement at various compression ratios. Manual as well as automatic methods of laryngeal parameter extraction are analyzed, including techniques based on spectral restriction applied to moderate-resolution RGB imagery (320x200 pixels). The analysis presented herein represents work-in-progress, and is not intended to represent a final implementation suitable for medical diagnostic or life-critical applications, but is advanced as a phenomenological overview of measurement error in the presence o

关键词： image compression laryngeal imaging optical metrology

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