Image quality assessment (IQA) is crucial in image processing algorithms. In the state-of-the-art IQA index, the structural similarity (SSIM) index has been proved to be better objective quality assessment metric. However, the accuracy of SSIM is relatively lacking when used to access blurred images. And the component weights of structural similarity (SSIM) index are fixed in some past environments. So an improved assessment algorithm incorporating multiple linear regressions and SSIM index was proposed in this paper. We use regression analysis to adjust the component weight of SSIM index. So the improved algorithm is more accuracy on different distortion types’ quality assessment. Experimental results show that the improved SSIM algorithm is better than traditional methods in nonlinear regression correlation coefficient, Spearman correlation coefficient and out ratio.
목차
Abstract 1. Introduction 2. Improved Image Quality Assessment Algorithm Based on Gradient and Structural Similarity 2.1. Gradient Component 2.2. Improved Image Quality Assessment Model Based on Gradient and Structural Similarity 3. Structural Similarity Index Method Integrated with Multiple Regression of Image Quality Assessment 3.1. Multiple Regression Analysis Theory 3.2. Structural Similarity Integrated with Multiple Regression Analysis of Image Evaluation Model 4. Experimental Results and Analysis 5. Conclusion References
키워드
image quality assessmentSSIMmultiple linear regressionsgradient
저자
Zhengyou Wang [ Shijiazhuang Tiedao University; 2, Jiangxi University of Finance & Economics No. 17 Northeast, Second Inner Ring Shijiazhuang, Hebei, P.R.C. 050043 ]
Corresponding Author
Liying Li [ Shijiazhuang Tiedao University; 2, Jiangxi University of Finance & Economics No. 17 Northeast, Second Inner Ring Shijiazhuang, Hebei, P.R.C. 050043 ]
Shuang Wu [ Jiangxi University of Finance & Economics No.169, East Shuanggang Road Changbei, Nanchang, Jiangxi, P.R.C. ]
Yanhui Xia [ Shijiazhuang Tiedao University; 2, Jiangxi University of Finance & Economics No. 17 Northeast, Second Inner Ring Shijiazhuang, Hebei, P.R.C. 050043 ]
Zheng Wan [ Jiangxi University of Finance & Economics No.169, East Shuanggang Road Changbei, Nanchang, Jiangxi, P.R.C. ]
Cong Cai [ Shijiazhuang Tiedao University; 2, Jiangxi University of Finance & Economics No. 17 Northeast, Second Inner Ring Shijiazhuang, Hebei, P.R.C. 050043 ]
보안공학연구지원센터(IJSIP) [Science & Engineering Research Support Center, Republic of Korea(IJSIP)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Signal Processing, Image Processing and Pattern Recognition
간기
격월간
pISSN
2005-4254
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.8 No.11