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David R. Comstock

dblp:203/6413 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1984
—ORCID · none

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

Computer networks · 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%
Theoretical computer science
1 paper
Coding theory · 100%
Computer networks
1 paper
Physical-layer communications · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video coding › transform coding
discrete cosine transform coding
0.011984
Hamming Coding of DCT-Compressed Images Over Noisy Channels · IEEE Trans. Commun. 1984
Image and video coding
transform coding
0.011984
Hamming Coding of DCT-Compressed Images Over Noisy Channels · IEEE Trans. Commun. 1984
Coding theory
error-correcting codes
0.011984
Hamming Coding of DCT-Compressed Images Over Noisy Channels · IEEE Trans. Commun. 1984
Coding theory › error-correcting codes
hamming codes
0.011984
Hamming Coding of DCT-Compressed Images Over Noisy Channels · IEEE Trans. Commun. 1984
Physical-layer communications › channel coding
binary symmetric channel
0.011984
Hamming Coding of DCT-Compressed Images Over Noisy Channels · IEEE Trans. Commun. 1984
Physical-layer communications
channel coding
0.011984
Hamming Coding of DCT-Compressed Images Over Noisy Channels · IEEE Trans. Commun. 1984

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

mean squared error analysis · 0.0bit allocation · 0.0
YearPublicationVenuePosition
1984 Hamming Coding of DCT-Compressed Images Over Noisy Channels
abstract
Theoretical and simulation results of using Hamming codes with the two-dimensional discrete cosine transform (2D-DCT) at a transmitted data rate of 1 bit/pixel over a binary symmetric channel (BSC) are presented. The design bit error rate (BER) of interest is 10-2. The (7, 4), (15, 11), and (31, 26) Hamming codes are used to protect the most important bits in each 16 by 16 transformed block, where the most important bits are determined by calculating the mean squared reconstruction error (MSE) contributed by a channel error in each individual bit. A theoretical expression is given which allows the number of protected bits to achieve minimum MSE for each code rate to be computed. By comparing these minima, the best code and bit allocation can be found. Objective and subjective performance results indicate that using the (7, 4) Hamming code to protect the most important 2D-DCT coefficients can substantially improve reconstructed image quality at a BER of 10-2. Furthermore, the allocation of 33 out of the 256 bits per block to channel coding does not noticeably degrade reconstructed image quality in the absence of channel errors.
David R. Comstock, Jerry D. Gibson
IEEE Trans. Commun.1