Lukáš Krasula

Performance evaluation of the emerging JPEG XT image compression standard

The upcoming JPEG XT is under development for High Dynamic Range (HDR) image compression. This standard encodes a Low Dynamic Range (LDR) version of the HDR image generated by a Tone-Mapping Operator (TMO) using the conventional JPEG coding as a base layer and encodes the extra HDR information in a residual layer. This paper studies the performance of the three profiles of JPEG XT (referred to as profiles A, B and C) using a test set of six HDR images. Four TMO techniques were used for the base layer image generation to assess the influence of the TMOs on the performance of JPEG XT profiles. Then, the HDR images were coded with different quality levels for the base layer and for the residual layer. The performance of each profile was evaluated using Signal to Noise Ratio (SNR), Feature SIMilarity Index (FSIM), Root Mean Square Error (RMSE), and CIEDE2000 color difference objective metrics. The evaluation results demonstrate that profiles A and B lead to similar saturation of quality at the higher bit rates, while profile C exhibits no saturation. Profiles B and C appear to be more dependent on TMOs used for the base layer compared to profile A.

On the accuracy of objective image and video quality models: New methodology for performance evaluation

There are several standard methods for evaluating the performance of models for objective quality assessment with respect to results of subjective tests. However, all of them suffer from one or more of the following drawbacks: They do not consider the uncertainty in the subjective scores, requiring the models to make certain decision where the correct behavior is not known. They are vulnerable to the quality range of the stimuli in the experiments. In order to compare the models, they require a mapping of predicted values to the subjective scores, thus not comparing the models exactly as they are used in the real scenarios. In this paper, new methodology for objective models performance evaluation is proposed. The method is based on determining the classification abilities of the models considering two scenarios inspired by the real applications. It does not suffer from the previously stated drawbacks and enables to easily evaluate the performance on the data from multiple subjective experiments. Moreover, techniques to determine statistical significance of the performance differences are suggested. The proposed framework is tested on several selected metrics and datasets, showing the ability to provide a complementary information about the models behavior while being in parallel with other state-of-the-art methods.

How to benchmark objective quality metrics from paired comparison data

The procedures commonly used to evaluate the performance of objective quality metrics rely on ground truth mean opinion scores and associated confidence intervals, which are usually obtained via direct scaling methods. However, indirect scaling methods, such as the paired comparison method, can also be used to collect ground truth preference scores. Indirect scaling methods have a higher discriminatory power and are gaining popularity, for example in crowdsourcing evaluations. In this paper, we present how the classification errors, an existing analysis tool, can also be used with subjective preference scores. Additionally, we propose a new analysis tool based on the receiver operating characteristic analysis. This tool can be used to further assess the performance of objective metrics based on ground truth preference scores. We provide a MATLAB script with an implementation of the proposed tools and we show one example of application of the proposed tools.

Quality Assessment of Sharpened Images: Challenges, Methodology, and Objective Metrics

Most of the effort in image quality assessment (QA) has been so far dedicated to the degradation of the image. However, there are also many algorithms in the image processing chain that can enhance the quality of an input image. These include procedures for contrast enhancement, deblurring, sharpening, up-sampling, denoising, transfer function compensation, and so on. In this paper, possible strategies for the QA of sharpened images are investigated. This task is not trivial, because the sharpening techniques can increase the perceived quality, as well as introduce artifacts leading to the quality drop (over-sharpening). Here, the framework specifically adapted for the QA of sharpened images and objective metrics comparison in this context is introduced. However, the framework can be adopted in other QA areas as well. The problem of selecting the correct procedure for subjective evaluation was addressed and a subjective test on blurred, sharpened, and over-sharpened images was performed in order to demonstrate the use of the framework. The obtained ground-truth data were used for testing the suitability of the state-of-the-art objective quality metrics for the assessment of sharpened images. The comparison was performed by novel procedure using rank order correlation analyses, which is found more appropriate for the task than standard methods. Furthermore, seven possible augmentations of the no-reference S3 metric adapted for sharpened images are proposed. The performance of the metric is significantly improved and also superior over the rest of the tested quality criteria with respect to the subjective data.

Evaluation of privacy in high dynamic range video sequences

The ability of high dynamic range (HDR) to capture details in environments with high contrast has a significant impact on privacy in video surveillance. However, the extent to which HDR imaging affects privacy, when compared to a typical low dynamic range (LDR) imaging, is neither well studied nor well understood. To achieve such an objective, a suitable dataset of images and video sequences is needed. Therefore, we have created a publicly available dataset of HDR video for privacy evaluation PEViD-HDR, which is an HDR extension of an existing Privacy Evaluation Video Dataset (PEViD). PEViD-HDR video dataset can help in the evaluations of privacy protection tools, as well as for showing the importance of HDR imaging in video surveillance applications and its influence on the privacy-intelligibility trade-off. We conducted a preliminary subjective experiment demonstrating the usability of the created dataset for evaluation of privacy issues in video. The results confirm that a tone-mapped HDR video contains more privacy sensitive information and details compared to a typical LDR video.

Influence of HDR reference on observers preference in tone-mapped images evaluation

The most reliable way to assess the quality of images after a dynamic range compression (i.e. tone-mapping) is a subjective study. The goal of this paper is to determine, whether the preference of the participating subjects is significantly affected by the presence of the original high dynamic range (HDR) image displayed on the HDR screen or if we can obtain equivalent results from the test without the reference. For that, an extensive experiment using two different setups has been performed. The statistical analysis showed significant difference between evaluations and a Monte Carlo simulation proved that the absence of the reference is the factor of influence.

Rendering of HDR content on LDR displays: an objective approach

Dynamic range compression (or tone mapping) of HDR content is an essential step towards rendering it on traditional LDR displays in a meaningful way. This is however non-trivial and one of the reasons is that tone mapping operators (TMOs) usually need content-specific parameters to achieve the said goal. While subjective TMO parameter adjustment is the most accurate, it may not be easily deployable in many practical applications. Its subjective nature can also influence the comparison of different operators. Thus, there is a need for objective TMO parameter selection to automate the rendering process. To that end, we investigate into a new objective method for TMO parameters optimization. Our method is based on quantification of contrast reversal and naturalness. As an important advantage, it does not require any prior knowledge about the input HDR image and works independently on the used TMO. Experimental results using a variety of HDR images and several popular TMOs demonstrate the value of our method in comparison to default TMO parameter settings.

An automated approach for tone mapping operator parameter adjustment in security applications

High Dynamic Range (HDR) imaging has been gaining popularity in recent years. Different from the traditional low dynamic range (LDR), HDR content tends to be visually more appealing and realistic as it can represent the dynamic range of the visual stimuli present in the real world. As a result, more scene details can be faithfully reproduced. As a direct consequence, the visual quality tends to improve. HDR can be also directly exploited for new applications such as video surveillance and other security tasks. Since more scene details are available in HDR, it can help in identifying/tracking visual information which otherwise might be difficult with typical LDR content due to factors such as lack/excess of illumination, extreme contrast in the scene, etc. On the other hand, with HDR, there might be issues related to increased privacy intrusion. To display the HDR content on the regular screen, tone-mapping operators (TMO) are used. In this paper, we present the universal method for TMO parameters tuning, in order to maintain as many details as possible, which is desirable in security applications. The method’s performance is verified on several TMOs by comparing the outcomes from tone-mapping with default and optimized parameters. The results suggest that the proposed approach preserves more information which could be of advantage for security surveillance but, on the other hand, makes us consider possible increase in privacy intrusion.

Preference of Experience in Image Tone-Mapping: Dataset and Framework for Objective Measures Comparison

The popularity of high dynamic range (HDR) imaging has grown in both academic and private research sectors. Since the native visualization of HDR content still has its limitations, the importance of dynamic range compression (i.e., tone-mapping) is very high. This paper evaluates observers’ preference of experience in context of image tone-mapping. Given the different nature of natural and computer-generated content, the way observers perceive the quality of tone-mapped images can be fundamentally different. In this paper, we describe a subjective experiment attempting to determine users’ preference with respect to these two types of content in two different viewing scenarios—with and without the HDR reference. The results show that the absence of the reference can significantly influence the subjects’ preferences for the natural images, while no significant impact has been found in the case of the synthetic images. Moreover, we introduce a benchmarking framework and compare the performance of selected objective metrics. The resulting dataset and framework are made publicly available to provide a common test bed and methodology for evaluating metrics in the considered scenario.

Objective evaluation of naturalness, contrast, and colorfulness of tone-mapped images

The main obstacle preventing High Dynamic Range (HDR) imaging from becoming standard in image and video processing industry is the challenge of displaying the content. The prices of HDR screens are still too high for ordinary customers. During last decade, a lot of effort has been dedicated to finding ways to compress the dynamic range for legacy displays with simultaneous preservation of details in highlights and shadows which cannot be achieved by standard systems. These dynamic range compression techniques are called tone-mapping operators (TMO) and introduce novel distortions such as spatially non-linear distortion of contrast or naturalness corruption. This paper provides an analysis of objective no-reference naturalness, contrast and colorfulness measures in the context of tone-mapped images evaluation. Reliable measures of these features could be further merged together into single overall quality metric. The main goal of the paper is to provide an initial study of the problem and identify the potential candidates for such a combination.