Adaptive constrained least square approach for removing blocking effect

Sung Wai Hong; Yuk Hee Chan; Wan Chi Siu

Adaptive constrained least square approach for removing blocking effect

Sung Wai Hong, Yuk Hee Chan, Wan Chi Siu

The Hong Kong Polytechnic University

Research output: Journal article publication › Conference article › Academic research › peer-review

4 Citations (Scopus)

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
Pages (from-to)	773-776
Number of pages	4
Journal	Proceedings - IEEE International Symposium on Circuits and Systems
Volume	2
Publication status	Published - 1 Jan 1995
Event	Proceedings of the 1995 IEEE International Symposium on Circuits and Systems-ISCAS 95. Part 3 (of 3) - Seattle, WA, United States Duration: 30 Apr 1995 → 3 May 1995

ASJC Scopus subject areas

Electrical and Electronic Engineering
Electronic, Optical and Magnetic Materials

Cite this

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title = "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 - Hong, Sung Wai

AU - Chan, Yuk Hee

AU - Siu, Wan Chi

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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.

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M3 - Conference article

SN - 0271-4310

VL - 2

SP - 773

EP - 776

JO - Proceedings - IEEE International Symposium on Circuits and Systems

JF - Proceedings - IEEE International Symposium on Circuits and Systems

T2 - Proceedings of the 1995 IEEE International Symposium on Circuits and Systems-ISCAS 95. Part 3 (of 3)

Y2 - 30 April 1995 through 3 May 1995

ER -

Adaptive constrained least square approach for removing blocking effect

Abstract

ASJC Scopus subject areas

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