The Experts below are selected from a list of 19545 Experts worldwide ranked by ideXlab platform
Doohee Jung - One of the best experts on this subject based on the ideXlab platform.
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jpeg quantization table design for photos with face in wireless handset
Advances in Multimedia, 2004Co-Authors: Gumin Jeong, Junho Kang, Yongsu Mun, Doohee JungAbstract:In this paper, a design technique of JPEG quantization table is proposed for photos with face whose size is 128 × 128 in wireless handset. The small size images may have different characteristics from the large images used in PC. Also, the photos with face have their own characteristics. From these two facts, new quantization table design is proposed in this paper. The quantization tables are derived from R-D optimization for the photos with face and it is shown that the proposed quantization tables have good performances for size and quality. In R-D optimization, the obtained quantization table is image-specific and cannot be applied to other images. In the proposed method, the quantization tables are obtained from various photo samples and final table is gotten as average of them. This makes the final quantization tables applied to other photos with face. Also, it is possible to control the quality factor based on the interpolation of high quality quantization table and middle quality quantization table. Simulation results show that the obtained quantization table makes the Compressed File size small and the image quality improved in general cases.
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PCM (3) - JPEG quantization table design for photos with face in wireless handset
Advances in Multimedia Information Processing - PCM 2004, 2004Co-Authors: Gumin Jeong, Junho Kang, Yongsu Mun, Doohee JungAbstract:In this paper, a design technique of JPEG quantization table is proposed for photos with face whose size is 128 × 128 in wireless handset. The small size images may have different characteristics from the large images used in PC. Also, the photos with face have their own characteristics. From these two facts, new quantization table design is proposed in this paper. The quantization tables are derived from R-D optimization for the photos with face and it is shown that the proposed quantization tables have good performances for size and quality. In R-D optimization, the obtained quantization table is image-specific and cannot be applied to other images. In the proposed method, the quantization tables are obtained from various photo samples and final table is gotten as average of them. This makes the final quantization tables applied to other photos with face. Also, it is possible to control the quality factor based on the interpolation of high quality quantization table and middle quality quantization table. Simulation results show that the obtained quantization table makes the Compressed File size small and the image quality improved in general cases.
Udi Manber - One of the best experts on this subject based on the ideXlab platform.
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A text compression scheme that allows fast searching directly in the Compressed File
ACM Transactions on Information Systems, 1997Co-Authors: Udi ManberAbstract:A new text compression scheme is presented in this article. The main purpose of this scheme is to speed up string matching by searching the Compressed File directly. The scheme requires no modification of the string-matching algorithm, which is used as a black box; any string-matching procedure can be used. Instead, the pattern is modified; only the outcome of the matching of the modified pattern against the Compressed File is deCompressed. Since the Compressed File is smaller than the original File, the search is faster both in terms of I/O time and precessing time than a search in the original File. For typical text Files, we achieve about 30% reduction of space and slightly less of search time. A 30% space saving is not competitive with good text compression schemes, and thus should not be used where space is the predominant concern. The intended applications of this scheme are Files that are searched often, such as catalogs, bibliographic Files, and address books. Such Files are typically not Compressed, but with this scheme they can remain Compressed indefinitely, saving space while allowing faster search at the same time. A particular application to an information retrieval system that we developed is also discussed.
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a text compression scheme that allows fast searching directly in the Compressed File
Combinatorial Pattern Matching, 1994Co-Authors: Udi ManberAbstract:A new text compression scheme is presented in this paper. The main purpose of this scheme is to speed up string matching by searching the Compressed File directly. The scheme requires no modification of the string-matching algorithm, which is used as a black box; any string-matching procedure can be used. Instead, the pattern is modified; only the outcome of the matching of the modified pattern against the Compressed File is deCompressed. Since the Compressed File is smaller than the original File, the search is faster both in terms of I/O time and processing time than a search in the original File. For typical text Files, we achieve about 30% reduction of space and slightly less of search time. A 30% space saving is not competitive with good text compression schemes, and thus should not be used where space is the predominant concern. The intended applications of this scheme are Files that are searched often, such as catalogs, bibliographic Files, and address books. Such Files are typically not Compressed, but with this scheme they can remain Compressed indefinitely, saving space while allowing faster search at the same time. A particular application to an information retrieval system that we developed is also discussed.
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CPM - A Text Compression Scheme That Allows Fast Searching Directly in the Compressed File
Combinatorial Pattern Matching, 1994Co-Authors: Udi ManberAbstract:A new text compression scheme is presented in this paper. The main purpose of this scheme is to speed up string matching by searching the Compressed File directly. The scheme requires no modification of the string-matching algorithm, which is used as a black box; any string-matching procedure can be used. Instead, the pattern is modified; only the outcome of the matching of the modified pattern against the Compressed File is deCompressed. Since the Compressed File is smaller than the original File, the search is faster both in terms of I/O time and processing time than a search in the original File. For typical text Files, we achieve about 30% reduction of space and slightly less of search time. A 30% space saving is not competitive with good text compression schemes, and thus should not be used where space is the predominant concern. The intended applications of this scheme are Files that are searched often, such as catalogs, bibliographic Files, and address books. Such Files are typically not Compressed, but with this scheme they can remain Compressed indefinitely, saving space while allowing faster search at the same time. A particular application to an information retrieval system that we developed is also discussed.
Teresa H. Meng - One of the best experts on this subject based on the ideXlab platform.
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Optimal quantizer step sizes for transform coders
[Proceedings] ICASSP 91: 1991 International Conference on Acoustics Speech and Signal Processing, 1991Co-Authors: A.c. Hung, Teresa H. MengAbstract:As evidenced by the theoretical modeling and simulation presented, the optimal quantizer solution for run-length and Huffman coding is quite addressable for the Laplacian case. The step sizes may be calculated in advance for images that share common statistics. Furthermore, the model can also be used for other uses such as bit-management for rate control and lower bound estimation for Compressed File sizes; it is also the first step in the general solution to the transform coder quantization problem. >
Gumin Jeong - One of the best experts on this subject based on the ideXlab platform.
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jpeg quantization table design for photos with face in wireless handset
Advances in Multimedia, 2004Co-Authors: Gumin Jeong, Junho Kang, Yongsu Mun, Doohee JungAbstract:In this paper, a design technique of JPEG quantization table is proposed for photos with face whose size is 128 × 128 in wireless handset. The small size images may have different characteristics from the large images used in PC. Also, the photos with face have their own characteristics. From these two facts, new quantization table design is proposed in this paper. The quantization tables are derived from R-D optimization for the photos with face and it is shown that the proposed quantization tables have good performances for size and quality. In R-D optimization, the obtained quantization table is image-specific and cannot be applied to other images. In the proposed method, the quantization tables are obtained from various photo samples and final table is gotten as average of them. This makes the final quantization tables applied to other photos with face. Also, it is possible to control the quality factor based on the interpolation of high quality quantization table and middle quality quantization table. Simulation results show that the obtained quantization table makes the Compressed File size small and the image quality improved in general cases.
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PCM (3) - JPEG quantization table design for photos with face in wireless handset
Advances in Multimedia Information Processing - PCM 2004, 2004Co-Authors: Gumin Jeong, Junho Kang, Yongsu Mun, Doohee JungAbstract:In this paper, a design technique of JPEG quantization table is proposed for photos with face whose size is 128 × 128 in wireless handset. The small size images may have different characteristics from the large images used in PC. Also, the photos with face have their own characteristics. From these two facts, new quantization table design is proposed in this paper. The quantization tables are derived from R-D optimization for the photos with face and it is shown that the proposed quantization tables have good performances for size and quality. In R-D optimization, the obtained quantization table is image-specific and cannot be applied to other images. In the proposed method, the quantization tables are obtained from various photo samples and final table is gotten as average of them. This makes the final quantization tables applied to other photos with face. Also, it is possible to control the quality factor based on the interpolation of high quality quantization table and middle quality quantization table. Simulation results show that the obtained quantization table makes the Compressed File size small and the image quality improved in general cases.
Wayne Wolf - One of the best experts on this subject based on the ideXlab platform.
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random access decompression using binary arithmetic coding
Data Compression Conference, 1999Co-Authors: Haris Lekatsas, Wayne WolfAbstract:We present an algorithm based on arithmetic coding that allows decompression to start at any point in the Compressed File. This random access requirement poses some restrictions on the implementation of arithmetic coding and on the model used. Our main application area is executable code compression for computer systems where machine instructions are deCompressed on-the-fly before execution. We focus on the decompression side of arithmetic coding and we propose a fast decoding scheme based on finite state machines. Furthermore, we present a method to decode multiple bits per cycle, while keeping the size of the decoder small.