image or datacompression is a frequent feature of modern computing and communication systems, and can be exploited continuously to increase overall processing efficiency via operations that process compressed data wi...
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image or datacompression is a frequent feature of modern computing and communication systems, and can be exploited continuously to increase overall processing efficiency via operations that process compressed data without decompression. In this work, it is demonstrated that processing can be used to provide a constant offset to the performance graph associated with Moore's Law, thus furnishing a fundamental practical increase in processing efficiency.
In this paper, a joint imagecompression and indexing technique using wavelet transform is presented. For compression, scalar quantization and classified vector quantization are applied in the wavelet domain to remove...
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In this paper, a joint imagecompression and indexing technique using wavelet transform is presented. For compression, scalar quantization and classified vector quantization are applied in the wavelet domain to remove redundancies from different sub-bands according to their distinct characteristics. For indexing, two statistical feature vectors are constructed directly from compression outputs (quantized sub-band data before entropy coding., which facilitate a hierarchical (coarser to finer) indexing procedure and achieve image indexing in the compressed domain. Experimental results show that the joint technique performs with equal effectiveness as either compression or indexing standing alone, while the computational cost for decompression is greatly reduced (only entropy decoding.is needed). Thus, the advantages of this joint (dual) imagecompression-indexing technique and its feasibility for online distributed image retrieval in the arena of exploding networked image applications are demonstrated.
An analysis of complexity and cost associated with object-based compression was carried out, in which each segmentable image region is viewed as a separate object. The predominant cost incurred by boundary representat...
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An analysis of complexity and cost associated with object-based compression was carried out, in which each segmentable image region is viewed as a separate object. The predominant cost incurred by boundary representation and compression, as opposed to the encoding.of texture, color, intensity, variance, position, and rotation information specific to the contents of each region was found. In preliminary tests using images of natural scenes and man-made objects, the imagecompression ratio (CR) was found to depend directly on the boundary compression ratio.
The pulse gating method is reformulated to generate a different form of side information that is much easier to compress. It is shown that this new side information can be simply and efficiently coded at a rate that c...
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The pulse gating method is reformulated to generate a different form of side information that is much easier to compress. It is shown that this new side information can be simply and efficiently coded at a rate that compares favorably with the empirically-estimated entropy of the original method.
An overview of motion detection, motion field computation and compression, and processing of compressed motion information is presented that is specific to video sequences of discrete imagery. Focus is on the classifi...
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An overview of motion detection, motion field computation and compression, and processing of compressed motion information is presented that is specific to video sequences of discrete imagery. Focus is on the classification of moving regions, features, or objects within a video sequence into three types of regions: (a) stationary, (b) periodic motion, and (c) aperiodic motion.
In this paper, a new encryption mode, which we call the 2D-encryption Mode, is presented. 2D-encryption Mode extends ID-encryption modes, as ECB, CBC and CTR, to two dimensions. It has good security and practical prop...
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In this paper, a new encryption mode, which we call the 2D-encryption Mode, is presented. 2D-encryption Mode extends ID-encryption modes, as ECB, CBC and CTR, to two dimensions. It has good security and practical properties. We first look at the type of problems it tries to solve, then describe the technique and its properties, and present a detailed mathematical analysis of its security, and finally discuss some practical issues related to its implementation.
Segmentation of images to bit planes is one of the techniques for scalable imagecompression. Assuming our source image to be from a uniform quantizer, we categorize its bit planes on the basis of their significance, ...
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Segmentation of images to bit planes is one of the techniques for scalable imagecompression. Assuming our source image to be from a uniform quantizer, we categorize its bit planes on the basis of their significance, into two groups called MSB-planes and LSB-planes. The MSB planes contain low-entropy structural information, whereas LSB planes contain high entropy texture information. Due to the different nature of information and entropy of the two groups, they can be coded and reconstructed by different algorithms. The structural nature of MSB planes, make them more compressible at entropy coding.stage, whereas the low significance of LSB-planes can be exploited against their high entropy. We realize the later by subsampling of LSB-planes, which in turn requires attention to the close coupling of MSB and LSB planes at the reconstruction stage. We introduce an estimation algorithm for the LSB planes. The reconstructed images are found to be perceptually comparable to the original images. Quantitative comparison also shows significant coding.gain in terms of SNR vs. bit rate.
A scheme for lossy hyperspectral data cube compression, using a linear mixing model approach and wavelet transform, is presented. The data is first compressed in the spectral dimension by using the linear mixing model...
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A scheme for lossy hyperspectral data cube compression, using a linear mixing model approach and wavelet transform, is presented. The data is first compressed in the spectral dimension by using the linear mixing model approximation to reduce the number of dimensions needed to represent the data. The reduced data is then compressed along the spatial dimensions using a wavelet transform. Five hyperspectral data cubes have been tested using the algorithm. compression ratios of up to 1000:1 are achieved with peak signal-to-noise (PSNR) ratios of over 40 dB. For all test cases, we were able to achieve ratios of over 200:1 with PSNR exceeding 46 dB. The ultra-high compression ratio with low distortion is an improvement over other results reported in the literature. In addition, the reconstructed spectra from the highly compressed file are shown to preserve the overall shape of the original spectra. However, in some cases the curves are slightly offset in some spectral regions from the original.
A novel rate-distortion optimization algorithm for JPEG 2000 is proposed. This algorithm meets memory buffer requirement for the compressed bit streams quite strictly according to a given bit rate. Moreover, before th...
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A novel rate-distortion optimization algorithm for JPEG 2000 is proposed. This algorithm meets memory buffer requirement for the compressed bit streams quite strictly according to a given bit rate. Moreover, before the encoding.process even starts, a required memory buffer size can be estimated. This algorithm can also help avoid unnecessary encoding.for some parts of an image. In this sense, it is memory efficient and performs progressive encoding. While a rate-distortion optimization algorithm is generally applied after complete encoding.procedures for images in JPEG 2000, the proposed algorithm can save both memory requirement and encoding.time significantly at low bit rate by avoiding complete encoding.
The proceedings contain 27 papers from the conference on mathematics of data/image coding. compression, and encryption IV, with Applications. The topics discussed include: improving wireless video communication withou...
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The proceedings contain 27 papers from the conference on mathematics of data/image coding. compression, and encryption IV, with Applications. The topics discussed include: improving wireless video communication without feedback information;analysis of digital chaotic optical signals;lossless datacompression in space amplifications;security analysis of public key watermarking schemes;dataencryption scheme with arithmetic coding.and robust digital watermarking using random casting method.
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