Evaluating image quality using consistent grey relational grade. Issue 2 (2014)

• Record Type: Journal Article
• Other Names: Special Editor.
• Is Part Of: Engineering computations. Volume 31:Issue 2(2014)
• Page Start: 231
• Page End: 249
• Publication Date: 2014
• Subjects: Consistent grey relational coefficient -- Consistent grey relational generating -- Consistent grey relational grade -- Contrast enhancement -- Image quality -- Multi‐criteria decision‐making; Computer-aided engineering -- Periodicals; Computer graphics -- Periodicals; 620.00285
• DOI: 10.1108/EC-01-2013-0016
• Languages: English
• ISSNs: 0264-4401

Abstract

Abstract : Purpose – Assessing image quality is a difficult task. Different demands need distinct criteria, so it is not realistic to decide which contrast enhancement method is better only through one criterion. The main purpose is to propose an efficient scheme to effectively evaluate image quality. Furthermore, the idea can be applied in other fields.Design/methodology/approach – To objectively and quantitatively assess image quality, the authors integrate four criteria into one composite criterion and use it to evaluate seven existing contrast enhancement methods. The mechanism of integration is through a newly proposed way of computing a grey relational grade (GRGd), called the consistent grey relational grade (CGRGd).Findings – In this paper, the authors propose the CGRGd, which is more efficient and consistent than other existing GRGds. When applied to image quality evaluation, the proposed CGRGd can effectively choose the best method than others. The results also indicate that the proposed CGRGd combined with appropriate criteria can be widely used in the field of multiple criteria.Originality/value – The proposed CGRGd is a new approach to the problem of multi‐criteria evaluation, and its application to the evaluation of image quality is a novel idea. For readers interested in the field of multi‐criteria decision‐making, the CGRGd provides an efficient and effective alternative. Acknowledgements : This work was supported by the National Science Council, Republic of China, under Grant NSC 101‐2221‐E‐040‐010.