Publication2016
Improving performance of K-SVD based image denoising using curvelet transform
The record
- Type
- Publication
- Date
- 10 June 2016
- Level
- National
- Journal
- 2015 International Conference on Microwave Optical and Communication Engineering Icmoce 2015
- Pages
- 381-384
- Published
- 10 June 2016
- DOI
- 10.1109/icmoce.2015.7489772
- Scopus ID
- 84979255967
- Authors
- 3
- Open access
- No
- Citations
- 17
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
K-SVD dictionary learning with curvelet transform for image denoising preserves texture features better than standard K-SVD, advancing signal processing research.
- Moderate confidence
- The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-3.2 Digital technology and artificial intelligence
Image processing algorithm innovation using sparse representation and transform domain techniques advances digital signal processing technology research.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
Evidence
Kortex hosts no documents. Evidence is an outbound link to the authority that holds it.
No outbound evidence link is recorded for this activity. The record below states which source it came from and when it was last read.
Provenance
Which source system this record came from, how many source rows were resolved into it, and when each was last read.
- Source rows resolved into this record
- 1
Each record carries the date Kortex last read it from its source system. That is a freshness date and not a verification: Kortex records what its sources say and when it read them, and it does not check those statements against any external authority. No claim on this site is described as verified, because none is.
Citing this record
This URL is stable. A record’s permalink is frozen when it is published and is not regenerated if its title is later corrected.
KIIT Deemed to be University. “Improving performance of K-SVD based image denoising using curvelet transform”. Kortex.