A quality metric based on a classification process is introduced. The main idea of the proposed method is to avoid the error pooling step of many factors (in frequential and spatial domain) commonly applied to obtain a final quality score. A classification process based on the Support Vector Machine method is designed to obtain the final quality class with respect to the standard quality scale ...

The video quality assessment must be adapted to the human visual system, which is why researchers have performed subjective viewing experiments in order to obtain the conditions of encoding of video systems to provide the best quality to the user. The objective of this study is to assess the video quality using image features extraction without using reference video. RMSE values and processing ...

Designing a reliable and generic perceptual quality metric is a challenging issue in three-dimensional (3D) visual signal processing. In many practical 3D application scenarios, the original stereoscopic images (i.e., the reference image) cannot be fully accessed, leaving difficulties to quality assessment. To handle this problem, 3D reduced-reference image quality assessment (RRIQA) metrics ha...

Reduced-reference (RR) image quality measures aim to predict the visual quality of distorted images with only partial information about the reference images. In this paper, we propose an RR image quality assessment method based on a natural image statistic model in the wavelet transform domain. We use the Kullback-Leibler distance between the marginal probability distributions of wavelet coeffi...

In this paper, a novel reduced reference (RR) stereoscopic image quality assessment (SIQA) is proposed by characterizing the statistical properties of the stereoscopic image in the reorganized discrete cosine transform (RDCT) domain. Firstly, the difference image between the left and right view images is computed. Afterwards, the left and right view images, as well as the difference image, are ...

Introduction: One of the major problems in the development of nuclear medicine images is the presence of noise. The noise level in nuclear medicine images is usually reduced by the analysis of imaging data in a Fourier transform environment. The main drawback of this environment belongs to low signal to noise ratio in high frequencies because removing noise frequencies may remove data and times...

Regarding the important constraints due to subjective quality assessment, objective image quality assessment has recently been extensively studied. Such metrics are usually of three kinds, they might be Full Reference (FR), Reduced Reference (RR) or No Reference (NR) metrics. We focus here on a new technique, which recently appeared in quality assessment context: data-hiding-based image quality...

In this paper, we introduce a Reduced Reference Image Quality Assessment (RRIQA) measure based on the natural image statistic approach. A new adaptive transform called ”Tetrolet” is applied to both reference and distorted images. To model the marginal distribution of tetrolet coefficients Bessel K Forms (BKF) density is proposed. Estimating the parameters of this distribution allows to summariz...

Objective image/video quality metrics which accurately represent the subjective quality of processed images are of paramount importance for the design and assessment of an image compression and transmission system. In some scenarios, it is also important to evaluate the quality of the received image with minimal reference to the transmitted one. For instance, for closed-loop optimization of a t...

Assessment for image quality traditionally needs its original image as a reference. The conventional method for assessment like Mean Square Error (MSE) or Peak Signal to Noise Ratio (PSNR) is invalid when there is no reference. In this paper, we present a new No-Reference (NR) assessment of image quality using blur and noise. The recent camera applications provide high quality images by help of...