JPEG-2000 is an emerging standard for still image compression. This paper provides a brief history of the JPEG-2000 standardization process, an overview of the standard, and some description of the capabilities provided by the standard. Part I of the JPEG-2000 standard specifies the minimum compliant decoder, while Part II describes optional, value-added extensions. Although the standard specifies only the decoder and bitstream syntax, in this paper we describe JPEG-2000 from the point of view of encoding. We take this approach, as we believe it is more amenable to a compact description more easily understood by most readers.

In this paper, we present the design, implementation and application of several families of fast multiplierless approximations of the discrete cosine transform (DCT) with the lifting scheme, named the binDCT. These binDCT families are derived from Chen's and Loeffler's plane rotation-based factorizations of the DCT matrix, respectively, and the design approach can also be applied to DCT of arbitrary size. Two design approaches are presented. In the first method, an optimization program is de ned, and the multiplierless transform is obtained by approximating its solution with dyadic values. In the second method, a general lifting-based scaled DCT structure is obtained, and the analytical values of all lifting parameters are derived, enabling dyadic approximations with different accuracies. Therefore the binDCT can be tuned to cover the gap between the Walsh-Hadamard transform and the DCT. The corresponding 2-D binDCT allows a 16-bit implementation, enables lossless compression, and maintai...

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This paper sheds light on the recent least-square (LS)-based adaptive prediction schemes for lossless compression of natural images. Our analysis shows that the superiority of the LS-based adaptation is due to its edge-directed property, which enables the predictor to adapt reasonably well from smooth regions to edge areas. Recognizing that LS-based adaptation improves the prediction mainly around the edge areas, we propose a novel approach to reduce its computational complexity with negligible performance sacrifice. The lossless image coder built upon the new prediction scheme has achieved noticeably better performance than the state-of-the-art coder CALIC with moderately increased computational complexity.

Abstract — In this paper, we survey some of the recent advances in lossless compression of continuoustone images. The modeling paradigms underlying the state-of-the-art algorithms, and the principles guiding their design, are discussed in a unified manner. The algorithms are described and experimentally compared. I.

We present a novel lossless (reversible) data embedding technique, which enables the exact recovery of the original host signal upon extraction of the embedded information. A generalization of the well-known LSB (least significant bit) modification is proposed as the data embedding method, which introduces additional operating points on the capacity-distortion curve. Lossless recovery of the original is achieved by compressing portions of the signal that are susceptible to embedding distortion, and transmitting these compressed descriptions as a part of the embedded payload. A prediction-based conditional entropy coder which utilizes unaltered portions of the host signal as side-information improves the compression e#ciency, and thus the lossless data embedding capacity.

Future lithography systems must produce more dense chips with smaller feature sizes, while maintaining the throughput of one wafer per sixty seconds per layer achieved by today's optical lithography systems. To achieve this throughput with a direct-write maskless lithography system, using 25 nm pixels for 50 nm feature sizes, requires data rates of about 10 Tb/s. In a previous paper, we presented an architecture which achieves this data rate contingent on consistent 25 to 1 compression of lithography data, and on implementation of a decoder-writer chip with a real-time decompressor fabricated on the same chip as the massively parallel array of lithography writers. In this paper, we examine the compression efficiency of a spectrum of techniques suitable for lithography data, including two industry standards JBIG and JPEG-LS, a wavelet based technique SPIHT, general file compression techniques ZIP and BZIP2, our own 2D-LZ technique, and a simple list-of-rectangles representation RECT. Layouts rasterized both to black-and-white pixels, and to 32 level gray pixels are considered. Based on compression efficiency, JBIG, ZIP, 2D-LZ, and BZIP2 are found to be strong candidates for application to maskless lithography data, in many cases far exceeding the required compression ratio of 25. To demonstrate the feasibility of implementing the decoder-writer chip, we consider the design of a hardware decoder based on ZIP, the simplest of the four candidate techniques. The basic algorithm behind ZIP compression is Lempel-Ziv 1977 (LZ77), and the design parameters of LZ77 decompression are optimized to minimize circuit usage while maintaining compression efficiency.

Abstract—In this letter we propose a new technique for progressive coding of hyperspectral data. Specifically, we employ a hybrid three-dimensional wavelet transform for spectral and spatial decorrelation in the framework of Part 2 of the JPEG 2000 standard. Both onboard and on-the-ground compression are addressed. The resulting technique is compliant with the JPEG 2000 family of standards and provides competitive performance with respect to state-of-the-art techniques. Index Terms—Three-dimensional set partitioning in hierarchical trees (3D-SPIHT), discrete wavelet transform (DWT), hyperspectral data, JPEG 2000, lossless and lossy compression, wavelet. I.

While many application service providers have proposed using thin-client computing to deliver computational services over the Internet, little work has been done to evaluate the effectiveness of thin-client computing in a wide-area network. To assess the potential of thin-client computing in the context of future commodity high-bandwidth Internet access, we have used a novel, noninvasive slow-motion benchmarking technique to evaluate the performance of several popular thin-client computing platforms in delivering computational services cross-country over Internet2. Our results show that using thin-client computing in a wide-area network environment can deliver acceptable performance over Internet2, even when client and server are located thousands of miles apart on opposite ends of the country. However, performance varies widely among thin-client platforms and not all platforms are suitable for this environment. While many thin-client systems are touted as being bandwidth efficient, we show that network latency is often the key factor in limiting wide-area thin-client performance. Furthermore, we show that the same techniques used to improve bandwidth efficiency often result in worse overall performance in wide-area networks. We characterize and analyze the different design choices in the various thin-client platforms and explain which of these choices should be selected for supporting wide-area computing services.

Recently, there have been a flurry of works on overcomplete motion compensated wavelet coding (OMCWC). In this paper, we address the importance of phase and focus on the design of scalable video coding algorithms within the OMCWC framework. Specifically, our new contributions consist of the following three components: 1) efficient block motion estimation techniques in the wavelet domain including hierarchical and fractional-pel block matching; 2) extend overcomplete motion compensated prediction (MCP) into overcomplete motion compensated temporal filtering (MCTF) to achieve temporal scalability; 3) context modeling strategies for embedded quantization and entropy coding of 3D wavelet coefficients. Experiment results are used to demonstrate that the class of overomplete MCP/MCTF coders are capable of achieving comparable performance to other competing interframe wavelet coders.