Azeddine Beghdadi

Image quality assessment using a neural network approach

In this paper, we propose a neural network approach to image quality assessment. In particular, the neural network measures the quality of an image by predicting the mean opinion score (MOS) of human observers, using a set of key features extracted from the original and test images. Experimental results, using 352 JPEG/JPEG2000 compressed images, show that the neural network outputs correlate highly with the MOS scores, and therefore, the neural network can easily serve as a correlate to subjective image quality assessment. Using 10-fold cross-validation, the predicted MOS values have a linear correlation coefficient of 0.9744, a Spearman ranked correlation of 0.9690, a mean absolute error of 3.75%, and an rms error of 4.77%. These results compare very favorably with the results obtained with other methods, such as the structural similarity index of Wang et al. [2004].

A noise-filtering method using a local information measure

A nonlinear-noise filtering method for image processing, based on the entropy concept is developed and compared to the well-known median filter and to the center weighted median filter (CWM). The performance of the proposed method is evaluated through subjective and objective criteria. It is shown that this method performs better than the classical median for different types of noise and can perform better than the CWM filter in some cases.

Entropic analysis of random morphologies

When the random morphology of ramified or percolating clusters exhibit local fluctuations, the framework of the theory of random percolation with its critical exponents and fractal dimension is still not enough to describe the disorder and the optical properties. We propose an alternative concept: the configuration entropy, that we compare to the multifractal analysis on computer simulated morphologies. At the percolation threshold, the entropy undergoes a maximum and its optimum length a minimum. In contrast with the multifractal analysis, the configuration entropy gives unambiguous results, relatively independent of the finite size of the image.

A new image distortion measure based on wavelet decomposition

This paper introduces a novel image distortion measure based on a nonredundant wavelet decomposition. The proposed image quality measure is compared with the PSNR and a previously introduced Wigner-Ville distribution-based measure on some real images and simulated degradations. The obtained results are assessed on the basis of consistency with the subjective quality assessment and the complexity of the measure.

Image fusion-based contrast enhancement

The goal of contrast enhancement is to improve visibility of image details without introducing unrealistic visual appearances and/or unwanted artefacts. While global contrast-enhancement techniques enhance the overall contrast, their dependences on the global content of the image limit their ability to enhance local details. They also result in significant change in image brightness and introduce saturation artefacts. Local enhancement methods, on the other hand, improve image details but can produce block discontinuities, noise amplification and unnatural image modifications. To remedy these shortcomings, this article presents a fusion-based contrast-enhancement technique which integrates information to overcome the limitations of different contrast-enhancement algorithms. The proposed method balances the requirement of local and global contrast enhancements and a faithful representation of the original image appearance, an objective that is difficult to achieve using traditional enhancement methods. Fusion is performed in a multi-resolution fashion using Laplacian pyramid decomposition to account for the multi-channel properties of the human visual system. For this purpose, metrics are defined for contrast, image brightness and saturation. The performance of the proposed method is evaluated using visual assessment and quantitative measures for contrast, luminance and saturation. The results show the efficiency of the method in enhancing details without affecting the colour balance or introducing saturation artefacts and illustrate the usefulness of fusion techniques for image enhancement applications.

Optical cross-over analysis of granular gold films at percolation

Abstract The optical properties of evaporated granular Au films at percolation are correlated to the electrical conductivity and morphological analysis. At percolation, the near infrared transmittance and reflectance, but also the optical absorption λ 2 /λ, become wavelength independent. This behaviour can be explained by scale considerations. Assuming the d.c. conduction to be governed by the free electrons present in the backbone, we demonstrate that all the free electrons present in the film contribute to its optical properties at percolation.

A survey of perceptual image processing methods

Perceptual approaches have been widely used in many areas of visual information processing. This paper presents an overview of perceptual based approaches for image enhancement, segmentation and coding. The paper also provides a brief review of image quality assessment (IQA) methods, which are used to evaluate the performance of visual information processing techniques. The intent of this paper is not to review all the relevant works that have appeared in the literature, but rather to focus on few topics that have been extensively researched and developed over the past few decades. The goal is to present a perspective as broad as possible on this actively evolving domain due to relevant advances in vision research and signal processing. Therefore, for each topic, we identify the main contributions of perceptual approaches and their limitations, and outline how perceptual vision has influenced current state-of-the-art techniques in image enhancement, segmentation, coding and visual information quality assessment.

LOCAL ENTROPY CHARACTERIZATION OF CORRELATED RANDOM MICROSTRUCTURES

A rigorous connection is established between the local porosity entropy introduced by Boger et al. (Physica A 187 (1992) 55) and the configurational entropy of Andraud et al. (Physica A 207 (1994) 208). These entropies were introduced as morphological descriptors derived from local volume fluctuations in arbitrary correlated microstructures occurring in porous media, composites or other heterogeneous systems. It is found that the entropy lengths at which the entropies assume an extremum become identical for high enough resolution of the underlying configurations. Several examples of porous and heterogeneous media are given which demonstrate the usefulness and importance of this morphological local entropy concept.

Entropic contrast enhancement

A technique for the contrast enhancement of a picture is proposed. The method is derived from the entropy concept of information theory. The originality of the algorithm rests on the use of a local contrast to define the digital entropy. The basic idea of the treatment is to enhance the contrast by transforming the global entropy. The same technique can also be used for an adaptive smoothing processing.

Natural enhancement of color image

A new algorithm of Natural Enhancement of Color Image (NECI) is proposed. It is inspired by multiscale Retinex model. There are four steps to realize this enhancement. At first, the image appearance is rendered by content-dependent global mapping for light cast correction, and then a modified Retinex filter is applied to enhance the local contrast. Histogram rescaling is used afterwards for normalization purpose. At last, the texture details of image are enhanced by emphasizing the high-frequency components of image using multichannel decomposition of Cortex Transform. In the contrast enhancement step, luminance channel is firstly enhanced, and then a weighing map is calculated by collecting luminance enhancement information and applied to chrominance channel in color space CIELCh which enables a proportional enhancement of chrominance. It avoids the problem of unbalanced enhancement in classical RGB independent channel operation. In this work, it is believed that image enhancement should avoid dramatic modifications to image such as light condition changes, color temperature alteration, or additional artifacts introduced or amplified. Disregarding light conditions of the scene usually leads to unnaturally sharpened images or dramatic white balance changes. In the proposed method, the ambience of image (warm or cold color impression) is maintained after enhancement, and no additional light sources are added to the scene, and no halo effect and blocking effect are amplified due to overenhancement. It realizes a Natural Enhancement of Color Image. Different types of natural scene images have been tested and an encouraging performance is obtained for the proposed method.