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Justin S. McMichael

dblp:06/3120 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2003
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 2

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
JPEG compression
0.012003
Recompression of JPEG images by requantization · IEEE Trans. Image Process. 2003
Image and video coding
perceptual quality optimization
0.012003
Recompression of JPEG images by requantization · IEEE Trans. Image Process. 2003
Image and video coding › quantization
requantization
0.012003
Recompression of JPEG images by requantization · IEEE Trans. Image Process. 2003

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

laplacian distribution modeling · 0.0discrete cosine transform analysis · 0.0
YearPublicationVenuePosition
2003 Recompression of JPEG images by requantization
abstract
In this paper, we report a novel heuristic for requantizing JPEG images. The resulting images are generally smaller and often have improved perceptual image quality over a "blind" requantization approach, that is, one that does not consider the properties of the quantization matrices. The heuristic is supported by a detailed mathematical treatment which incorporates the well-known Laplacian distribution of the AC discrete cosine transform (DCT) coefficients with an analysis of the error introduced by requantization. We note that the technique is applicable to any image compression method which employs discrete cosine transforms and quantization.
Heinz H. Bauschke, Chris H. Hamilton, Mason S. Macklem, Justin S. McMichael, Nicholas R. Swart
IEEE Trans. Image Process.4
2002 A requantization-based method for recompressing JPEG images
abstract
We propose a new method for requantizing JPEG images, based on the well-known Laplacian distribution of the AC discrete cosine transform (DCT) coefficients and on an analysis of the error introduced by requantization. The resulting images have improved perceptual image quality over a “blind” requantization approach, that is, one that does not consider the properties of the quantization matrices.
Heinz H. Bauschke, Chris H. Hamilton, Mason S. Macklem, Justin S. McMichael, Nicholas R. Swart
ICASSP4