Why Shape Coding? Asymptotic Analysis of the Entropy Rate for Digital Images
This paper focuses on the ultimate limit theory of image compression. It proves that for an image source, there exists a coding method with shapes that can achieve the entropy rate under a certain condition where the shape-pixel ratio in the encoder/decoder is <inline-formula><math xmlns=&q...
Main Authors: | Gangtao Xin, Pingyi Fan, Khaled B. Letaief |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-12-01
|
Series: | Entropy |
Subjects: | |
Online Access: | https://www.mdpi.com/1099-4300/25/1/48 |
Similar Items
-
Normal approximation and asymptotic expansions /
by: Bhattacharya, R. N. (Rabindra Nath), 1937-, et al.
Published: (1976) -
Asymptotically Exact Constants in Natural Convergence Rate Estimates in the Lindeberg Theorem
by: Ruslan Gabdullin, et al.
Published: (2021-03-01) -
Soft Compression for Lossless Image Coding Based on Shape Recognition
by: Gangtao Xin, et al.
Published: (2021-12-01) -
Sharp Second-Order Pointwise Asymptotics for Lossless Compression with Side Information
by: Lampros Gavalakis, et al.
Published: (2020-06-01) -
Periodic solutions and asymptotic behavior for continuous algebraic difference equations
by: El Hadi Ait Dads, et al.
Published: (2017-07-01)