182 research outputs found
Grouping strategies to improve the correlation between subjective and objective image quality data
No full textThe aim of our research is to specify experimentally and further model spatial frequency response functions, which quantify human sensitivity to spatial information in real complex images. Three visual response functions are measured: the isolated Contrast Sensitivity Function (iCSF), which describes the ability of the visual system to detect any spatial signal in a given spatial frequency octave in isolation, the contextual Contrast Sensitivity Function (cCSF), which describes the ability of the v isual system to detect a spatial signal in a given octave in an image and the contextual Visual Perception Function (VPF), which describes visual sensitivity to changes in suprathreshold contrast in an image. In this paper we present relevant background, along with our first attempts to derive experimentally and further model the VPF and CSFs. We examine the contrast detection and discrimination frameworks developed by Barten, which we find prov ide a sound starting position for our own modeling purposes. Progress is presented in the following areas: verification of the chosen model for detection and discrimination; choice of contrast metrics for defining contrast sensitivity; apparatus, laboratory set-up and imaging system characterization; stimuli acquisition and stimuli variations; spatial decomposition; methodology for subjective tests. Initial iCSFs are presented and compared with 'classical' findings that hav e used simple visual stimuli, as well as with more recent relevant work in the literature. © 2013 SPIE-IS&T
Noisy images-JPEG compressed: subjective and objective image quality evaluation
No full textThe aim of this work is to study image quality of both single and multiply distorted images. We address the case of images corrupted by Gaussian noise or JPEG compressed as single distortion cases and images corrupted by Gaussian noise and then JPEG compressed, as multiply distortion case. Subjective studies were conducted in two parts to obtain human judgments on the single and multiply distorted images. We study how these subjective data correlate with No Reference state-of-the-art quality metrics. We also investigate proper combining of No Reference metrics to achieve better performance. Results are analyzed and compared in terms of correlation coefficients
Adaptive contrast enhancement for underexposed images
No full textIn the present article we focus on enhancing the contrast of images with low illumination that present large underexposed regions. For these particular images, when applying the standard contrast enhancement techniques, we also introduce noise over-enhancement within the darker regions. Even if both the contrast enhancement and denoising problems have been widely addressed within the literature, these two processing steps are, in general, independently considered in the processing pipeline. The goal of this work is to integrate contrast enhancement and denoise algorithms to proper enhance the above described type of images. The method has been applied to a proper database of underexposed images. Our results have been qualitatively compared before and after applying the proposed algorithm. © 2011 SPIE-IS&T
Searching through photographic databases with QuickLook
No full textG. Ciocca, C. Cusano, R. Schettini, S. Santini, A. de Polo, F. Tavanti, “Searching through photographic databases with QuickLook”. Proc. Multimedia on Mobile Devices 2012; and Multimedia Content Access: Algorithms and Systems VI. Ed- Reiner Creutzburg; David Akopian; Cees G. M. Snoek; Nicu Sebe; Lyndon Kennedy. 8304. 83040V-1 (2012). Copyright 2012 Society of Photo‑Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.We present here the results obtained by including a new image descriptor, that we called prosemantic feature vector, within the framework of QuickLook2 image retrieval system. By coupling the prosemantic features and the relevance feedback mechanism provided by QuickLook2, the user can move in a more rapid and precise way through the feature space toward the intended goal. The prosemantic features are obtained by a two-step feature extraction process. At the first step, low level features related to image structure and color distribution are extracted from the images. At the second step, these features are used as input to a bank of classifiers, each one trained to recognize a given semantic category, to produce score vectors. We evaluated the efficacy of the prosemantic features under search tasks on a dataset provided by Fratelli Alinari Photo Archive.© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only
A recall or precision oriented skin classifier using binary combining strategies
No full textSkin detection is a preliminary step in several applications, and many different methods are available in the literature. We show that the performance of explicit skin cluster classifiers can be enhanced by preprocessing the images with a white balance algorithm. Different combining strategies are then applied to these binary classifiers to further improve their performance in terms of recall and/or precision. Experimental results on a large and heterogeneous image database are presented
No reference image quality classification for JPEG-distorted images
No full textIn this paper, we address the Image Quality Assessment (IQA) of JPEG-distorted images. We approach the IQA field by focusing on a classification problem that maps different objective metrics into different categorical quality classes. To this end, we adopt a machine learning classification approach, where No Reference (NR) metrics are considered as features, while the assigned classes come from psycho-visual experiments. Eleven NR metrics have been considered: seven specific for blockiness and four general purpose. We evaluate the performance of single metrics and investigate if a pool of metrics can reach better performances than each of the single ones. Five as well as three quality classes are considered, and the corresponding classifiers are tested on two well known databases available in the literature (LIVE and MICT), and on a new database (IVL) presented in this paper
Pixel based skin colour classification exploiting explicit skin cluster definition methods
No full textIn this paper we examine the performance, on a large and heterogeneous image database, of
various skin detectors based on explicit colour skin cluster definition, coupled with a cast remover to see whether, and to what degree, the effectiveness of classification is improved, regardless of the
strategy adopted. We also evaluate the hypothesis that a combination of some of the skin detection algorithms studied could ensure a more accurate classification than any of the algorithms provides individually. Different combination rules have been investigated. All the experiments have been performed on the Compaq skin database. The results are evaluated in terms of both recall (the ratio
between the number of skin pixels correctly classified and the total number of actual skin pixels), and precision (the ratio between the number of skin pixels correctly classified and the total number of
pixels labelled as skin pixels by the detection method employed)
Adaptive edge enhancement using a neurodynamical model of visual attention
No full textA new approach for selective edge enhancement using unsharp masking is presented. This is based on the premise that biological vision and image reproduction share common principles. In the traditional approach the high frequency components of the image are emphasized, adding to the signal a constant fraction of its high-pass filtered version. The presence of a linear high-pass filter makes the system extremely sensitive to noise. In our approach, the high frequencies added to input image are weighted by a topographic map corresponding to visually salient regions, obtained by a neurodynamical model of visual attention. In this way, the unsharp masking algorithm becomes local and adaptive, enhancing differently the edges according to human perception
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