An adaptive constrained least square approach for removing blocking effect

S.W. Hong; Yuk Hee Chan; W.C. Siu

An adaptive constrained least square approach for removing blocking effect

S.W. Hong, Yuk Hee Chan, W.C. Siu

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research

Abstract

This paper presents a new adaptive objective function based on the regularized iterative block reduction technique for low-bit rate transform coded images. Also, a better initial estimate for the regularization approach is presented. Two types of prior knowledge are used: the first type bounds the maximum tolerable error (roughness), and the second type restricts the high-frequency content (smoothness) of the restored images. Computer simulations showed that the new adaptive objective function with the proposed initial estimate performed better on both subjective and objective measures than did a previously proposed objective function.

Original language	English
Title of host publication	[Missing Source Name from PIRA]
Publisher	IEEE
ISBN (Print)	0780321278
Publication status	Published - 1995

Keywords

Computational complexity
Computer simulation
Constraint theory
Estimation
Functions
Image compression
Image reconstruction
Least squares approximations

More information

http://hdl.handle.net/10397/1507

Cite this

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title = "An adaptive constrained least square approach for removing blocking effect",

abstract = "This paper presents a new adaptive objective function based on the regularized iterative block reduction technique for low-bit rate transform coded images. Also, a better initial estimate for the regularization approach is presented. Two types of prior knowledge are used: the first type bounds the maximum tolerable error (roughness), and the second type restricts the high-frequency content (smoothness) of the restored images. Computer simulations showed that the new adaptive objective function with the proposed initial estimate performed better on both subjective and objective measures than did a previously proposed objective function.",

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AU - Chan, Yuk Hee

AU - Siu, W.C.

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N2 - This paper presents a new adaptive objective function based on the regularized iterative block reduction technique for low-bit rate transform coded images. Also, a better initial estimate for the regularization approach is presented. Two types of prior knowledge are used: the first type bounds the maximum tolerable error (roughness), and the second type restricts the high-frequency content (smoothness) of the restored images. Computer simulations showed that the new adaptive objective function with the proposed initial estimate performed better on both subjective and objective measures than did a previously proposed objective function.

AB - This paper presents a new adaptive objective function based on the regularized iterative block reduction technique for low-bit rate transform coded images. Also, a better initial estimate for the regularization approach is presented. Two types of prior knowledge are used: the first type bounds the maximum tolerable error (roughness), and the second type restricts the high-frequency content (smoothness) of the restored images. Computer simulations showed that the new adaptive objective function with the proposed initial estimate performed better on both subjective and objective measures than did a previously proposed objective function.

KW - Computational complexity

KW - Computer simulation

KW - Constraint theory

KW - Estimation

KW - Functions

KW - Image compression

KW - Image reconstruction

KW - Least squares approximations

M3 - Conference article published in proceeding or book

SN - 0780321278

BT - [Missing Source Name from PIRA]

PB - IEEE

ER -

An adaptive constrained least square approach for removing blocking effect

Abstract

Keywords

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