Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 483

The DOI matches its Crossref record.

The LOT: transform coding without blocking effects

Malvar, H.S., Staelin, D.H.·1989·IEEE Transactions on Acoustics, Speech, and Signal Processing

Abstract

An exact derivation of an optimal lapped orthogonal transform (LOT) is presented. The optimal LOT is related to the discrete cosine transform (DCT) in such a way that a fast algorithm for a nearly optimal LOT is derived. Compared to the DCT, the fast LOT requires about 20-30% more computations, mostly additions. An image coding example demonstrates the effectiveness of the LOT in reducing blocking effects; the LOT actually leads to slightly smaller signal reconstruction errors than does the DCT.>

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1109/29.17536

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

Metadata

Authors
Malvar, H. S., & Staelin, D. H.
Venue
IEEE Transactions on Acoustics, Speech, and Signal Processing
Published
1989-04
Volume
37
Issue
4
Pages
553-559
ISSN
0096-3518 (ISSN-L)
OpenAlex
W2115002753
Cited by
483
References
0
FWCI
14.73
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.