Image quality analysis

Shankar, Krishnan. (2009) Image quality analysis. [Final Year Project Report] (Unpublished)

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Abstract

Image quality analysis is becoming more an d more important in this digital age. The main objective of image quality analysis is to study the quality of image s and develop methods to efficiently and swiftly determine the quality of images. This project aims to study subjective and obj e ctive assessm ent methods of image quality as well as to draw correlations between each objective assessment and the subjective assessment. Three objective assessment methods were used in this project, the Quality Index algorithm developed by Zhou Wang and Alan C. B ovik , the Peak Signal - to - Noise Ratio ( PSNR ) Bl ock - Set, and the Mean Squared Error ( MSE ) calculating algorithm. By doing so, a better understanding of what is actually required to develop an efficient image quality assessment method was gained. The resulting da ta also indicated what type of objective assessment was most suitable for which type of impairment imposed upon an image. Finally, the conclusions of this study were used to develop a prototype of a neural network based image quality assessment method that could be further enhanced as part of a further study to eve ntually develop an objective image quality analysis method that has a higher correlation to the subjective assessment method compared to the other objective assessment methods employed throughout this project.

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