Analysis of anisotropic blind image quality assessment

Abstract

Understanding quality of an image is a challenging task in absence of good quality reference image in many applications. In degraded image it is often assume that structure of image remains same so the objective of Blind Image Quality Assessment (BIQI) is to detect the structural degradation which is orientation dependent so blind quality of an image can be analyzed through anisotropic measure of an image. This thesis analyzes one of such Blind Image Quality Index (BIQI) measure like Anisotropic Blind Quality Index (ABQI). ABQI is measured by calculating standard deviation using Renyi entropy and directional pseudo wigner distribution. A standard database, Laboratory for Image & Video Engineering (LIVE) database is used to analyse the ABQI algorithm. The algorithm is validated by Spearman and Pearson correlation coefficients. The result provides a way of identifying best quality and noise free images from other degraded versions, allowing an automatic and non-reference classification of images according to their relative quality. It is also shown that the anisotropic measure is well correlated with classical reference metrics such as the Structural Similarity Index Measure (SSIM).