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Vishwas Udpikar

dblp:48/764 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 1994
—ORCID · none

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

Artificial intelligence and machine learning · 1Computer networks · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 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 · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video coding › image compression › lossy image compression
block truncation coding
0.011987
BTC Image Coding Using Vector Quantization · IEEE Trans. Commun. 1987
Image and video coding
image compression
0.011987
BTC Image Coding Using Vector Quantization · IEEE Trans. Commun. 1987
Image and video coding › quantization
vector quantization
0.011987
BTC Image Coding Using Vector Quantization · IEEE Trans. Commun. 1987
Image and video coding
bit rate reduction
0.011987
BTC Image Coding Using Vector Quantization · IEEE Trans. Commun. 1987

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

vector quantization · 0.0
YearPublicationVenuePosition
1994 A text-to-speech system for application by visually handicapped and illiterate
P. Bhaskararao, Venkata N. Peri, Vishwas Udpikar
ICSLP3
1987 BTC Image Coding Using Vector Quantization
abstract
This paper describes source encoding of the outputs of a block truncation coder (BTC), namely, the overhead statistical information and the truncated block. The statistical overhead and the truncated block exhibit properties which can be effectively used for their quantization as vectors. Vector quantization of these BTC outputs results into reduction of the bit rate of the coder. The bit rate reduces up to 1.5 bits/ pel if vector quantization is used on one of the outputs; i.e., either the overhead information or the truncated block. By vector quantizing both the BTC outputs the bit rate can he reduced up to 1.0 bits/pel without introducing many perceivable errors in the reconstructed output.
Vishwas Udpikar, J. P. Raina
IEEE Trans. Commun.1