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Measurement of visual quality is of significant importance to many image processing tasks. The target of image quality assessment (IQA) is to design effective computational models in order to automatically predict the quality of images in a perceptual consistent manner. We propose a full reference (FR) IQA metric based on information-theoretic IQA framework and passive aggressive learning algorithm...
In this work, several state-of-the-art Blind Image Quality Assessment (IQA) metrics and measures are evaluated in order to verify how they behave on extreme conditions such as the ones found on pictures of metallic surfaces. This is an important research topic given that the automation of the image acquisition comprehends one of the essential steps towards the automation and autonomy in many fields...
In this letter, a novel no reference image quality metric is developed, a set of ten features are extracted from each distorted image, then Relevance Vector Machine algorithm (RVM) is utilized to learn the mapping between the combined features and human opinion scores, experiments are conducted on the LIVE databases. The performance of the proposed metric is compared with some existing NR metrics...
In this paper, we propose a computational strategy to enhance the performance of Image Quality Metrics (IQM) by using content specific features of an image. We do this by creating Visual Error Importance (VEI) map that is applied to the error maps computed by the IQM. A global optimization can be used to compute the VEI map that is optimal for any given IQM. We demonstrate this concept by categorizing...
In free viewpoint television (FTV) application scenario, views that synthesized with depth image-based rendering (DIBR) techniques mainly contain special artifacts like geometric distortions. These artifacts may affect the structure of images/videos by changing the global contour characteristics and thus are annoying for human observers. Context tree based contour coding scheme can be a good tool...
Contrast is a very important characteristic for visual perception of image quality. Some No-Reference Image Quality Assessment Algorithm NR-IQA metrics for Contrast-Distorted Images (CDI) have been proposed in the literature, e.g. Reduced-reference Image Quality Metric for Contrast-changed images (RIQMC) and NR-IQA for Contrast-Distorted Images (NR-IQACDI). Here, we intend to improve the assessment...
As an emissive display, the organic light emitting diode (OLED) endure an indispensable role on the market growth of consumer electronics. Despite the preferable power efficiency, the active matrix OLED (AMOLED) displays still consume large energy. To adaptively increase the power efficiency of AMOLED displays, we propose an adjustable pixel dimming algorithm based on the structural similarity metric...
The problem of measuring the contrast of image elements (objects and background) for complex monochrome images is considered in this paper. A new method for measuring the contrast of image elements is proposed on the basis of analytical assessments of the contrast of the corresponding elements of the initial and inverted images. The new definitions for weighted and relative contrast of image elements...
Quality assessment of ultrasound images is difficult since image quality is subjective to the human observer. Nevertheless, image quality metrics are imperative when benchmarking different beamforming techniques. However, if we do not know how a beamformer alters an image, a quality metric might give an incorrect measurement of the image quality. Using the standard Delay-And-Sum (DAS) beamformer as...
The quality assessment of edges in an image is an important topic as it helps to benchmark the performance of edge detectors, and edge-aware filters that are used in a wide range of image processing tasks. The most popular image quality metrics such as Mean squared error (MSE), Peak signal-to-noise ratio (PSNR) and Structural similarity (SSIM) metrics for assessing and justifying the quality of edges...
Face recognition-based authentication techniques can be easily spoofed using various types of attack. Consistent counter-measures need to meet certain requirements, mainly regarding reliable robustness and low complexity. In this paper, we aim to find the best compromise between these two criteria, as we propose an anti-spoofing solution based on Image Quality Assessment (IQA) to distinguish between...
Image quality assessment (IQA) plays a crucial role in monitoring quality control in image communication systems, and in benchmarking and optimizing parameters in enhancement algorithms. The full-reference IQA metrics require a good-quality reference image, obtaining which may not be practical in real-life applications. This paper, therefore, proposes a no-reference IQA metric based on the hypothesis...
Manifold causes of image blurring make the no-reference evaluation of realistic blurred images very challenging. Previous studies indicate that handcrafted features suffer from poor representation of the intrinsic characteristics of image blurring and thus blind image sharpness assessment (BISA) is unsatisfactory. This paper explores a shallow convolutional neural network (CNN) to address this problem...
Image blurriness or definition is an important indicator to assess the quality of digital image. The objective no-reference image blur metric plays significant roles in the design and optimization of visual perception-based auto-focus systems as well as image acquisition, transmission, enhancement, restoration and compression algorithms. In this paper, we proposed a novel no-reference image blur metric...
This paper proposes an image quality assessment method based on visual saliency and gradient amplitude. Multi-scale decomposition is used, then with the analysis of the image's phase spectrum in frequency domain, the visual saliency map can be obtained. Meanwhile, the gradient amplitude map is obtained through analyzing the image's contrast feature. The weighted products of the visual saliency map...
the task of full-focused digital images construction relates to computational photography and is a process of increasing the information capacity of images obtained via photo- and video-fixation devices with limited optical depth of field. Additional to this task is the question of automatic evaluation of the quality of the images. The most popular non-reference metrics for comparing the quality of...
Multiview video plus depth (MVD) is the most popular 3D video format where the texture images contain the color information and the depth maps represent the geometry of the scene. The depth maps are exploited to obtain intermediate views to enable 3D-TV and free-viewpoint applications using the depth image based rendering (DIBR) techniques. DIBR is used to get an estimate of the intermediate views...
Stereoscopic vision is a complex system which receives and integrates perceptual information from both monocular and binocular cues. In this paper, a novel reduced-reference stereoscopic image quality assessment scheme is proposed, based on the visual perceptual information measured by entropy of classified primitives (EoCP) and mutual information of classified primitives (MIoCP), named as DCprimary,...
Free view point video (FVV), which offers immersive experience to users with multiple views, is one of the new trends in advanced visual media. These new viewpoints are traditionally synthesized via depth image-based rendering(DIBR) and geometric distortions are therefore observed. Mid-level contours descriptors are capable of evaluating such edges incoherence among the synthesized images which common...
In this paper, a new method with visual saliency detection for image quality assessment (IQA) is proposed. Through the experiments in this paper, we have verified the proposed method can be effective than most others.
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