A. K. Pal

dblp:25/6460 · DBLP profile ↗
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3ranked-venue papers
0as first author
2since 2021 · last 2024
—ORCID · none

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

Artificial intelligence and machine learning · 2 · 2 since 2021Graphics, 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 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video coding
image compression
0.112011
An Improved Image Compression Algorithm Using Binary Space Partition Scheme and Geometric Wavelets · IEEE Trans. Image Process. 2011
Image and video coding › image compression
wavelet-based image coding
0.112011
An Improved Image Compression Algorithm Using Binary Space Partition Scheme and Geometric Wavelets · IEEE Trans. Image Process. 2011

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

slope intercept representation · 0.1geometric wavelet · 0.1binary space partition · 0.1
YearPublicationVenuePosition
2024 Prospect-regret theory based decision-making approach for incomplete probabilistic hesitant fuzzy environment: An application to medical field
Garima Bisht, A. K. Pal
Expert Syst. Appl.2
2021 A hybrid fuzzy COPRAS-base-criterion method for multi-criteria decision making
Monika Narang, M. C. Joshi, A. K. Pal
Soft Comput.3
2011 An Improved Image Compression Algorithm Using Binary Space Partition Scheme and Geometric Wavelets
abstract
Geometric wavelet is a recent development in the field of multivariate nonlinear piecewise polynomials approximation. The present study improves the geometric wavelet (GW) image coding method by using the slope intercept representation of the straight line in the binary space partition scheme. The performance of the proposed algorithm is compared with the wavelet transform-based compression methods such as the embedded zerotree wavelet (EZW), the set partitioning in hierarchical trees (SPIHT) and the embedded block coding with optimized truncation (EBCOT), and other recently developed "sparse geometric representation" based compression algorithms. The proposed image compression algorithm outperforms the EZW, the Bandelets and the GW algorithm. The presented algorithm reports a gain of 0.22 dB over the GW method at the compression ratio of 64 for the Cameraman test image.
Garima Chopra, A. K. Pal
IEEE Trans. Image Process.2