Showing papers by "Katsumi Tanaka published in 1995"
TL;DR: Novel tools from finite group theory are applied to derive a compact form of representation for permutation, called permutation-cyclic-representation (PCR) vectors, with which various regularities and constraints in the structure of positional information are displayed, whereby the coding is made very easy using a runlength and Huffman method.
Abstract: We present the theory and practice of permutation coding as a new tool for very low-bit-rate image compression. Conventional source coding deals with the data information of signals, while the permutation coding achieves compression through efficiently representing the positional information (i.e., position permutation) caused by ordering the data information into order statistics. A set of four theorems is presented. The first one reveals the information-theoretic relationship between data and permutation information and the rest solves the efficient coding problem. For this, novel tools from finite group theory are applied to derive a compact form of representation for permutation, called permutation-cyclic-representation (PCR) vectors, with which various regularities and constraints in the structure of positional information are displayed, whereby the coding is made very easy using a runlength and Huffman method. A block DCT-based permutation coding algorithm (the BCPC) is developed attempting to combine the DCT's excellent features of energy packing and magnitude ordering that are found to be amenable to permutation coding. This mutually beneficial characteristic significantly reduces the coding bit-rate. Simulation results are provided for real images, showing an improvement by 3-4 dB in the peak-SNR index as compared to those representing the state-of-the-art.
12 citations
Journal Article•
7 citations
Proceedings Article•
11 Apr 1995
TL;DR: A mechanism for incremental data organization of semi-structured data in handling ancient Chinese document data to support scientists’ incremental and hypothetical work processes (object/type identification, classification and verification/abstraction from users’ multiple viewpoints) is introduced.
Abstract: In this paper, we introduce a mechanism for incremental data organization of semi-structured data in handling ancient Chinese document data. The objective of the mechanism is to support scientists’ incremental and hypothetical work processes (object/type identification, classification and verification/abstraction from users’ multiple viewpoints). We have developed a prototype incremental database system based on an Object-Oriented DBMS, Gemstone. The mechanisms realized by our system are (1) an instance-based data model which allows class extensions of heterogeneous objects, multiple class memberships and multiple roles of instances, and incremental object/schema evolution, (2) anchor object definition and manipulation, which enables users to define any fragments of text data as independent objects at run-time, (3) an active rule mechanism for enforcing the integrity constraints of the class membership of heterogeneous objects, and incremental schema/object generation, and (4) data set analyzing tool for data sets, which generates an intensional representation for a given data set to verify the validity of classification works and/or to discover concepts.
2 citations
TL;DR: In this article, the notion of interval queries on object histories is introduced and conditions are provided under which an interval query applied to object histories described by one "computational-tuple sequence scheme" yields, as its answer, the set of all object histories which can be described by another CSS.
1 citations
01 Jan 1995
TL;DR: Novel tools from finite group theory are applied to derive a compact form of representation for permutation, called permutation-cyclic-reprsentation (PCR)- vectors, with which various regularities and constraints in the structure of positional information are displayed, whereby the coding is made very easy using a rnnlength and Huffman method.
Abstract: We present the theory and practice of permutation coding as a new tool for very low-bit-rate image compression. Conventional source coding deals with the data information of signals, while the permutation coding achieves compression through efficiently representing the positional information (Le., position permutation) caused by ordering the data information into order statistics. A set of four theorems is presented. The first one reveals the information-theoretic relationship between data and permutation information and the rest solves the ef- ficient coding problem. For this, novel tools from finite group theory are applied to derive a compact form of representation for permutation, called permutation-cyclic-reprsentation (PCR)- vectors, with which various regularities and constraints in the structure of positional information are displayed, whereby the coding is made very easy using a rnnlength and Huffman method. A block DCT-based permutation coding algorithm (the BCPC) is developed attempting to combine DCT's excellent features of energy packing and magnitude ordering that are found to be amenable to the permutation coding. This mutually benefitial characteristic significantly reduces the coding bit-rate. Simulation results are provided for real images, showing an improvement by 3-4 dB in the peak-SNR index as compared to those representing the state-of-the-art.