Terahertz Security Image Quality Assessment by No-reference Model Observers

To provide the possibility of developing objective image quality assessment (IQA) algorithms for THz security images, we constructed the THz security image database (THSID) including a total of 181 THz security images with the resolution of 127*380. The main distortion types in THz security images were first analyzed for the design of subjective evaluation criteria to acquire the mean opinion scores. Subsequently, the existing no-reference IQA algorithms, which were 5 opinion-aware approaches viz., NFERM, GMLF, DIIVINE, BRISQUE and BLIINDS2, and 8 opinion-unaware approaches viz., QAC, SISBLIM, NIQE, FISBLIM, CPBD, S3 and Fish_bb, were executed for the evaluation of the THz security image quality. The statistical results demonstrated the superiority of Fish_bb over the other testing IQA approaches for assessing the THz image quality with PLCC (SROCC) values of 0.8925 (-0.8706), and with RMSE value of 0.3993. The linear regression analysis and Bland-Altman plot further verified that the Fish__bb could substitute for the subjective IQA. Nonetheless, for the classification of THz security images, we tended to use S3 as a criterion for ranking THz security image grades because of the relatively low false positive rate in classifying bad THz image quality into acceptable category (24.69%). Interestingly, due to the specific property of THz image, the average pixel intensity gave the best performance than the above complicated IQA algorithms, with the PLCC, SROCC and RMSE of 0.9001, -0.8800 and 0.3857, respectively. This study will help the users such as researchers or security staffs to obtain the THz security images of good quality. Currently, our research group is attempting to make this research more comprehensive.Comment: 13 pages, 8 figures, 4 table

A MONOTONICITY MEASURE WITH A FAST ALGORITHM FOR OBJECTIVE EVALUATION OF TONE MAPPING METHODS

The range of light intensity in the real world greatly exceeds what most existing devices can display. Various tone mapping methods have been developed to render HDR (high dynamic range) images or to increase local contrast of conventionally captured images. While local (or spatially varying) tone mapping methods are generally more effective they are also prone to artifacts such as halos. Most existing methods for evaluating tone-mapped images focus on preservation of informative details and may not identify artifacts effectively. This paper proposes an objective metric based on a monotonicity measure that may serve as a baseline measure for artifacts due to intensity reversal. A naïve method to compute the metric has a high computational complexity of O(N2), where N is the total number of pixels. To make the metric acceptable for interactive applications, a fast algorithm with the complexity of O(N) is presented. Experimental results using real-world images are included to demonstrate the efficacy of both the metric and the fast algorithm

Underwater image quality assessment: subjective and objective methods

Underwater image enhancement plays a critical role in marine industry. Various algorithms are applied to enhance underwater images, but their performance in terms of perceptual quality has been little studied. In this paper, we investigate five popular enhancement algorithms and their output image quality. To this end, we have created a benchmark, including images enhanced by different algorithms and ground truth image quality obtained by human perception experiments. We statistically analyse the impact of various enhancement algorithms on the perceived quality of underwater images. Also, the visual quality provided by these algorithms is evaluated objectively, aiming to inform the development of objective metrics for automatic assessment of the quality for underwater image enhancement. The image quality benchmark and its objective metric are made publicly available

Visibility and distortion measurement for no-reference dehazed image quality assessment via complex contourlet transform

Recently, most dehazed image quality assessment (DQA) methods mainly focus on the estimation of remaining haze, omitting the impact of distortions from the side effect of dehazing algorithms, which lead to their limited performance. Addressing this problem, we proposed a learning both Visibility and Distortion Aware features no-reference (NR) Dehazed image Quality Assessment method (VDA-DQA). Visibility aware features are exploited to characterize clarity optimization after dehazing, including the brightness, contrast, and sharpness aware feature extracted by complex contourlet transform (CCT). Then, distortion aware features are employed to measure the distortion artifacts of images, including the normalized histogram of local binary pattern (LBP) from the reconstructed dehazed image and the statistics of the CCT sub-bands corresponding to chroma and saturation map. Finally, all the above features are mapped into the quality scores by the support vector regression (SVR). Extensive experimental results on six public DQA datasets verify the superiority of proposed VDA-DQA in terms of the consistency with subjective visual perception, and outperforms the state-of-the-art methods.The source code of VDA-DQA is available at https://github.com/li181119/VDA-DQA

Quality assessment metric of stereo images considering cyclopean integration and visual saliency

This paper was accepted for publication in the journal Information Sciences and the definitive published version is available at http://dx.doi.org/10.1016/j.ins.2016.09.004.In recent years, there has been great progress in the wider use of three-dimensional (3D) technologies. With increasing sources of 3D content, a useful tool is needed to evaluate the perceived quality of the 3D videos/images. This paper puts forward a framework to evaluate the quality of stereoscopic images contaminated by possible symmetric or asymmetric distortions. Human visual system (HVS) studies reveal that binocular combination models and visual saliency are the two key factors for the stereoscopic image quality assessment (SIQA) metric. Therefore inspired by such findings in HVS, this paper proposes a novel saliency map in SIQA metric for the cyclopean image called “cyclopean saliency”, which avoids complex calculations and produces good results in detecting saliency regions. Moreover, experimental results show that our metric significantly outperforms conventional 2D quality metrics and yields higher correlations with human subjective judgment than the state-of-art SIQA metrics. 3D saliency performance is also compared with “cyclopean saliency” in SIQA. It is noticed that the proposed metric is applicable to both symmetric and asymmetric distortions. It can thus be concluded that the proposed SIQA metric can provide an effective evaluation tool to assess stereoscopic image quality

Local tone mapping operator for detail preserving reproduction of high dynamic range images.

Opseg osvetljaja koji se javlja u prirodnim scenama uveliko prevazilazi mogućnosti standardnih uređaja za snimanje i reprodukciju slike. Ljudski vizuelni sistem je evoluirao, tako da omogući efikasno funkcionisanje i percepciju detalja u uslovima velike promene osvetljaja. Kako bi se omogućila što realnija reprodukcija slika i video sadržaja, potrebno je obezbediti mogućnost snimanja i reprodukcije što šireg dinamičkog opsega osvetljaja. Razvoj tehnika za snimanje je napredovao i danas postoji mogućnost snimanja celokupnog dinamičkog opsega osvetljaja scene korišćenjem standardnih senzora. Razvoj displeja je međutim napredovao sporije i većina displeja koji su danas u upotrebi ima skroman dinamički opseg osvetljaja. Operator za redukciju dinamičkog opsega predstavlja ključnu komponentu sistema za reprodukciju scena širokog dinamičkog opsega (HDR), na standardnim displejima nižeg dinamičkog opsega (LDR)...Light intensity variations in natural scenes greatly exceed the capabillities of standard imaging and display devices. The human visual system has evolved to deal with these lightning conditions and enable efficient perception of details. In order to enable realistic reproduction of natural images and video, it is necessary to develop techniques and devices for capturing and reproduction of the high dynamic range content. Capturing techniques have evolved and now it is possible to capture entire dynamic range of the scene using standard sensors. The development of displays, however, has progressed more slowly and most of the displays that are used today exhibits modest dynamic range capabilities. Tone mapping operator is a key component that enables reproduction of the high dynamic range (HDR) images on the low dynamic range (LDR) displays..