1990
DOI: 10.1109/42.57766
|View full text |Cite
|
Sign up to set email alerts
|

Variable rate vector quantization for medical image compression

Abstract: Three techniques for variable-rate vector quantizer design are applied to medical images. The first two are extensions of an algorithm for optimal pruning in tree-structured classification and regression due to Breiman et al. The code design algorithms find subtrees of a given tree-structured vector quantizer (TSVQ), each one optimal in that it has the lowest average distortion of all subtrees of the TSVQ with the same or lesser average rate. Since the resulting subtrees have variable depth, natural variable-r… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
35
0
1

Year Published

1994
1994
2008
2008

Publication Types

Select...
5
2
1

Relationship

1
7

Authors

Journals

citations
Cited by 78 publications
(36 citation statements)
references
References 21 publications
0
35
0
1
Order By: Relevance
“…In the first case, an additional (L+l) log ( N / L + l ) bits are required to specify the count and the reproduction vector (centroid) of the left child t L . This accounts for the remaining terms in (8). From this information, the decoder can derive the count and centroid of the right child t R by ntR = nt -ntL and w t R = (ntut-ntLwtL)/ntR.…”
Section: At + Xtrec(t) Zand(xn St!)mentioning
confidence: 99%
See 2 more Smart Citations
“…In the first case, an additional (L+l) log ( N / L + l ) bits are required to specify the count and the reproduction vector (centroid) of the left child t L . This accounts for the remaining terms in (8). From this information, the decoder can derive the count and centroid of the right child t R by ntR = nt -ntL and w t R = (ntut-ntLwtL)/ntR.…”
Section: At + Xtrec(t) Zand(xn St!)mentioning
confidence: 99%
“…First, the centroid of the entire data sequence is transmitted using L log ( N / L + l ) bits. This is the reproduction vector used at the root, and accounts for the first term in (8). With this initial tree TO, the decoder can already begin reconstructing the received image.…”
Section: At + Xtrec(t) Zand(xn St!)mentioning
confidence: 99%
See 1 more Smart Citation
“…A great many vector-quantization approaches have been proposed for image compression by several researchersÐLinde et al (1980), Gray (1984), Chang et al (1988), Netravali (1988), Gersho and Gray (1992), Riskin et al (1990), Yair et al (1992), , and Andrew and Palaniswami (1996). In addition, neural-network-based techniques have been used to address vector quantization.…”
Section: Introductionmentioning
confidence: 99%
“…A great deal of literature based on vector quantization has been discussed in other articles. 2,4,9,10,14,[17][18][19]24,28 The goal of vector quantization is to create a codebook for which the average distortion generated by a training vector and a codevector in codebook is minimized. The minimization of average distortion is widely used by a gradient descent-based iterative procedure.…”
Section: Introductionmentioning
confidence: 99%