We propose a natural scene statistic-based distortion-generic blind/no-reference (NR)
image quality assessment (IQA) model that operates in the spatial domain. The new model …

Blind image quality assessment (BIQA) aims to evaluate the perceptual quality of a distorted
image without information regarding its reference image. Existing BIQA models usually …

In this paper, we present an efficient general-purpose objective no-reference (NR) image
quality assessment (IQA) framework based on unsupervised feature learning. The goal is to …

General purpose blind image quality assessment (BIQA) has been recently attracting
significant attention in the fields of image processing, vision and machine learning. Stateof …

We propose a natural scene statistic based Blind/Referenceless Image Spatial QUality
Evaluator (BRISQUE) which extracts the point wise statistics of local normalized luminance …

This paper presents an algorithm designed to measure the local perceived sharpness in an
image. Our method utilizes both spectral and spatial properties of the image: For each block …

The goal of no-reference objective image quality assessment (NR-IQA) is to develop a
computational model that can predict the human-perceived quality of distorted images …

In this letter, we present a simple, yet effective wavelet-based algorithm for estimating both
global and local image sharpness (FISH, Fast Image Sharpness). FISH operates by first …

Blind image quality assessment (BIQA) is an important yet difficult task in image processing
related applications. Existing algorithms for universal BIQA learn a mapping from features of …

This specification describes technologies relating to biometric authentication based on
images of the eye. In general, one aspect of the subject matter described in this specification …