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Jun-Ichi Matsunaga

dblp:51/9703 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1983
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Image and video coding · 67% Image and video processing · 33%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video coding › image compression
bilevel image coding
0.011983
Depth-First Picture Expression Viewed from Digital Picture Processing · IEEE Trans. Pattern Anal. Mach. Intell. 1983
Image and video coding
bit-plane coding
0.011983
Depth-First Picture Expression Viewed from Digital Picture Processing · IEEE Trans. Pattern Anal. Mach. Intell. 1983

Methods — techniques the papers use, named apart from their topics

depth-first picture expression · 0.0bit-plane coding · 0.0
YearPublicationVenuePosition
1983 Depth-First Picture Expression Viewed from Digital Picture Processing
abstract
A picture coding strategy titled DF-expression (Depth-First picture expression) is now studied from another point of view. The basic idea of DF-expression is briefly reviewed at first. Its capability in data compression is demonstrated using 1024 × 1024 binary pictures. Then the new aspects of DF-expression are studied in reference to picture processing algorithm on the coded form. They include circular shiftings, spectrum of primitives, logical operations, etc. Application of DF-expression to gray images (or multivalued pictures) is the next topics of the paper. DF-expression is applicable to bit-plane coding of any binary image data. Our conclusion with this point is that the gray code is the best binary code system for DF-expression in information preserving sense. Information-lossy type data reduction is another topics in this paper. The authors propose a new data reduction technique in terms of uniformalization of excessively complicated regions in bit-planes. Experimental study follows using a 256 × 256 sized fourbit test picture. Finally, conclusions and other possibility of the applications are remarked.
Eiji Kawaguchi, Tsutomu Endo, Jun-Ichi Matsunaga
IEEE Trans. Pattern Anal. Mach. Intell.3