With an increased interest in applications that require a clean background image, such as video surveillance, object tracking, street view imaging and location-based services on web-based maps, multiple algorithms have been developed to reconstruct a background image from cluttered scenes. Traditionally, statistical measures and existing image quality techniques have been applied for evaluating...

290 Abstract: Critical image processing tasks can be efficiently executed by fusion of images taken from range of distributed sensors. Advancements in digital image processing and communication technology with invent of new sensors experiencing the excessive need of effective image quality assessment of image fusion techniques. Various metrics have been discussed for quality measurement of fuse...

OBJECTIVE Different technical and procedural methods have been introduced to develop low radiation dose protocols in neurointerventional examinations. We investigated the feasibility of minimizing radiation exposure dose by simply decreasing the detector dose during cerebral DSA and evaluated the comparative level of image quality using both subjective and objective methods. METHODS In a pros...

Biometric sample quality assessment approaches are generally designed in terms of utility property due to the potential difference between human perception of quality and the biometric quality requirements for a recognition system. This study proposes a utility based quality assessment method of fingerprints by considering several complementary aspects: 1) Image quality assessment without any r...

Image quality assessment (IQA) is a complex problem due to subjective nature of human visual perception. Human have always seen the world in color. The widely objective metrics used are mean squared error (MSE), peak signal to noise ratio (PSNR), and human visual system based on structural similarity and edge based similarity. The problem of these objective metrics that they evaluate the qualit...

A crucial step in image compression is the evaluation of its performance, and more precisely, available ways to measure the quality of compressed images. In this paper, a machine learning expert, providing a quality score is proposed. This quality measure is based on a learned classification process in order to respect human observers. The proposed method namely Machine Learning-based Image Qua...

This paper presents a novel method of no-reference image quality assessment for JPEG encoded images by means of multiresolution analysis using Haar wavelet decomposition. The proposed method takes advantage of the fact that JPEG encoded images are usually contaminated with blockiness artifacts. Blockiness artifact is modeled as a particular edge structure that transforms into a different edge s...

A blind/no-reference (NR) method is proposed in this paper for image quality assessment (IQA) of the images compressed in discrete cosine transform (DCT) domain. When an image is measured by structural similarity (SSIM), two variances, i.e. mean intensity and variance of the image, are used as features. However, the parameters of original copies are actually unavailable in NR applications; henc...

This paper presents a full-reference (FR) image quality assessment (IQA) method based on a deep convolutional neural network (CNN). The CNN extracts features from distorted and reference image patches and estimates the quality of the distorted ones by combining and regressing the feature vectors using two fully connected layers. Experiments are performed on the LIVE and TID2013 databases and co...