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Michael B. Martin

dblp:43/172 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2001
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author

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 · 100%

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

TopicWeightPapersLastEvidence papers
Image and video coding
image compression
0.012001
New image compression techniques using multiwavelets and multiwavelet packets · IEEE Trans. Image Process. 2001
Image and video coding › image compression
wavelet-based image coding
0.012001
New image compression techniques using multiwavelets and multiwavelet packets · IEEE Trans. Image Process. 2001
Image and video coding
transform coding
0.012001
New image compression techniques using multiwavelets and multiwavelet packets · IEEE Trans. Image Process. 2001

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

quantization · 0.0multiwavelet transform · 0.0
YearPublicationVenuePosition
2001 New image compression techniques using multiwavelets and multiwavelet packets
abstract
Advances in wavelet transforms and quantization methods have produced algorithms capable of surpassing the existing image compression standards like the Joint Photographic Experts Group (JPEG) algorithm. For best performance in image compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry. However, the design possibilities for wavelets are limited because they cannot simultaneously possess all of the desirable properties. The relatively new field of multiwavelets shows promise in obviating some of the limitations of wavelets. Multiwavelets offer more design options and are able to combine several desirable transform features. The few previously published results of multiwavelet-based image compression have mostly fallen short of the performance enjoyed by the current wavelet algorithms. This paper presents new multiwavelet transform and quantization methods and introduces multiwavelet packets. Extensive experimental results demonstrate that our techniques exhibit performance equal to, or in several cases superior to, the current wavelet filters.
Michael B. Martin, Amy E. Bell
IEEE Trans. Image Process.1