Author: Kede Ma Publisher: ISBN: Category : Languages : en Pages : 58
Book Description
Tone mapping operators aim to compress high dynamic range (HDR) images to low dynamic range ones so as to visualize HDR images on standard displays. Most existing works were demonstrated on specific examples without being thoroughly tested on well-established and subject-validated image quality assessment models. A recent tone mapped image quality index (TMQI) made the first attempt on objective quality assessment of tone mapped images. TMQI consists of two fundamental building blocks: structural fidelity and statistical naturalness. In this thesis, we propose an enhanced tone mapped image quality index (eTMQI) by 1) constructing an improved nonlinear mapping function to better account for the local contrast visibility of HDR images and 2) developing an image dependent statistical naturalness model to quantify the unnaturalness of tone mapped images based on a subjective study. Experiments show that the modified structural fidelity and statistical naturalness terms in eTMQI better correlate with subjective quality evaluations. Furthermore, we propose an iterative optimization algorithm for tone mapping. The advantages of this algorithm are twofold: 1) eTMQI and TMQI can be compared in a more straightforward way; 2) better quality tone mapped images can be automatically generated by using eTMQI as the optimization goal. Numerical and subjective experiments demonstrate that eTMQI is a superior objective quality assessment metric for tone mapped images and consistently outperforms TMQI.
Author: Xihe Gao Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
High dynamic range (HDR) images provide the capacity to represent the luminance in real scenes with much higher precision than standard image formats. With advances in hardware and computer graphics technologies, HDR images are rapidly becoming more commonplace. To visualize HDR images on contemporary display devices, the dynamic range needs to be adapted to the much smaller range of the devices. This is accomplished through tone mapping, with the goal of reproducing the visual appearance of HDR scenes. Tone mapping has attracted much attention and several dozens of tone mapping operators have been proposed. Nevertheless, it remains challenging to objectively evaluate the quality of tone mapped images and optimize tone mapping operators with automated algorithms. Using virtual photographs to bridge the gap of dynamic ranges for feature analysis, we propose two feature-based quality metrics for tone mapped images, which measure the distortion of important image features that affect the perceived quality. We present an image quality metric called visual saliency distortion predictor (VSDP) that measures the distortion in visual saliency for quality assessment. Additionally, by incorporating multiple feature-based measures to predict the quality of tone mapped images, we introduce another quality metric: perceptual distortion predictor (PDP). Subjective and numerical experiments indicate that the proposed feature-based quality metrics can yield more reliable prediction than the alternative approaches. Once suitable quality metrics are defined, there emerges an opportunity to automate the tuning of existing tone mapping operators. By minimizing the distortion in visual saliency predicted by the quality metric VSDP, we developed an automatic parameter tuning algorithm for tone mapping operators. Moreover, based on the quality prediction of PDP, we propose an automated blended tone mapping algorithm which blends images from multiple operators with varying weights to leverage the strengths of each of operators considered. Experiments with a broad range of HDR images and statistical analysis demonstrate the effectiveness of the tone mapping optimization algorithms.
Author: Hojatollah Yeganeh Publisher: ISBN: Category : Languages : en Pages : 127
Book Description
In recent years, image and video signals have become an indispensable part of human life. There has been an increasing demand for high quality image and video products and services. To monitor, maintain and enhance image and video quality objective image and video quality assessment tools play crucial roles in a wide range of applications throughout the field of image and video processing, including image and video acquisition, communication, interpolation, retrieval, and displaying. A number of objective image and video quality measures have been introduced in the last decades such as mean square error (MSE), peak signal to noise ratio (PSNR), and structural similarity index (SSIM). However, they are not applicable when the dynamic range or spatial resolution of images being compared is different from that of the corresponding reference images. In this thesis, we aim to tackle these two main problems in the field of image quality assessment. Tone mapping operators (TMOs) that convert high dynamic range (HDR) to low dynamic range (LDR) images provide practically useful tools for the visualization of HDR images on standard LDR displays. Most TMOs have been designed in the absence of a well-established and subject-validated image quality assessment (IQA) model, without which fair comparisons and further improvement are difficult. We propose an objective quality assessment algorithm for tone-mapped images using HDR images as references by combining 1) a multi-scale signal fidelity measure based on a modified structural similarity (SSIM) index; and 2) a naturalness measure based on intensity statistics of natural images. To evaluate the proposed Tone-Mapped image Quality Index (TMQI), its performance in several applications and optimization problems is provided. Specifically, the main component of TMQI known as structural fidelity is modified and adopted to enhance the visualization of HDR medical images on standard displays. Moreover, a substantially different approach to design TMOs is presented, where instead of using any pre-defined systematic computational structure (such as image transformation or contrast/edge enhancement) for tone-mapping, we navigate in the space of all LDR images, searching for the image that maximizes structural fidelity or TMQI. There has been an increasing number of image interpolation and image super-resolution (SR) algorithms proposed recently to create images with higher spatial resolution from low-resolution (LR) images. However, the evaluation of such SR and interpolation algorithms is cumbersome. Most existing image quality measures are not applicable because LR and resultant high resolution (HR) images have different spatial resolutions. We make one of the first attempts to develop objective quality assessment methods to compare LR and HR images. Our method adopts a framework based on natural scene statistics (NSS) where image quality degradation is gauged by the deviation of its statistical features from NSS models trained upon high quality natural images. In particular, we extract frequency energy falloff, dominant orientation and spatial continuity statistics from natural images and build statistical models to describe such statistics. These models are then used to measure statistical naturalness of interpolated images. We carried out subjective tests to validate our approach, which also demonstrates promising results. The performance of the proposed measure is further evaluated when applied to parameter tuning in image interpolation algorithms.
Author: Chenwei Deng Publisher: Springer ISBN: 3319103687 Category : Technology & Engineering Languages : en Pages : 311
Book Description
This book provides comprehensive coverage of the latest trends/advances in subjective and objective quality evaluation for traditional visual signals, such as 2D images and video, as well as the most recent challenges for the field of multimedia quality assessment and processing, such as mobile video and social media. Readers will learn how to ensure the highest storage/delivery/ transmission quality of visual content (including image, video, graphics, animation, etc.) from the server to the consumer, under resource constraints, such as computation, bandwidth, storage space, battery life, etc.
Author: Frédéric Dufaux Publisher: Academic Press ISBN: 0128030399 Category : Computers Languages : en Pages : 631
Book Description
At the time of rapid technological progress and uptake of High Dynamic Range (HDR) video content in numerous sectors, this book provides an overview of the key supporting technologies, discusses the effectiveness of various techniques, reviews the initial standardization efforts and explores new research directions in all aspects involved in HDR video systems. Topics addressed include content acquisition and production, tone mapping and inverse tone mapping operators, coding, quality of experience, and display technologies. This book also explores a number of applications using HDR video technologies in the automotive industry, medical imaging, spacecraft imaging, driving simulation and watermarking. By covering general to advanced topics, along with a broad and deep analysis, this book is suitable for both the researcher new or familiar to the area. With this book the reader will: Gain a broad understanding of all the elements in the HDR video processing chain Learn the most recent results of ongoing research Understand the challenges and perspectives for HDR video technologies Covers a broad range of topics encompassing the whole processing chain in HDR video systems, from acquisition to display Provides a comprehensive overview of this fast emerging topic Presents upcoming applications taking advantages of HDR
Author: Hanning Yuan Publisher: Springer ISBN: 9811039666 Category : Computers Languages : en Pages : 644
Book Description
The two volume proceedings of CCIS 698 and 699 constitutes revised selected papers from the 4th International Conference on Geo-Informatics in Resource Management and Sustainable Ecosystem, GRMSE 2016, held in Hong Kong, China, in November 2016. The total of 118 papers presented in these proceedings were carefully reviewed and selected from 311 submissions. The contributions were organized in topical sections named: smart city in resource management and sustainable ecosystem; spatial data acquisition through RS and GIS in resource management and sustainable ecosystem; ecological and environmental data processing and management; advanced geospatial model and analysis for understanding ecological and environmental processes; applications of geo-informatics in resource management and sustainable ecosystem.
Author: Dohyoung Lee Publisher: ISBN: Category : Languages : en Pages :
Book Description
Quality assessment of image data plays a vital role in various applications, e.g., the evaluation and optimization of visual processing algorithms and the monitoring of visual communication systems. Although subjective assessment is the most reliable means to measure image quality, it is not always feasible in practical applications. Therefore, objective image quality metrics (IQMs) that can accurately predict the subjective judgments of average human observers have gained considerable attentions from research community. In the past few decades, numerous IQMs have been proposed to estimate the perceived quality of visual data. Depending on the availability of a reference (i.e., perfect quality) image to compare with, they can be categorized into full-reference (FR) and no-reference (NR) IQMs. Most existing IQMs are designed to rely on image features in the grayscale domain. Despite their reasonable performance in dealing with traditional distortions (e.g. additive white Gaussian noise or Gaussian blur), such grayscale IQMs tend to underestimate the visual disturbance caused by chromatic distortions, e.g., degradation caused from color gamut mapping or tone mapping algorithms. This study proposes new color IQMs capable of handling image data exhibiting both chromatic and achromatic distortions by incorporating perceptual color attributes, e.g., hue and chroma. Both FR and NR IQMs are introduced for different target applications. In particular, the proposed solutions properly process directional hue data using directional statistical tools, addressing the general limitation of existing approaches that treating hue data as linear data. Extensive validation performed on large-scale databases demonstrates the proposed IQMs correlate well with the subjective ratings over commonly encountered chromatic and achromatic distortions, indicating that the appropriate handling of highly informative hue data improves the prediction accuracy of color IQMs. These promising results indicate that they can be deployed on a wide range of color image processing problems as generalized quality assessment solutions.
Author: Mohamed Kamel Publisher: Springer Science & Business Media ISBN: 3642215920 Category : Computers Languages : en Pages : 467
Book Description
The two-volume set LNCS 6753/6754 constitutes the refereed proceedings of the 8th International Conference on Image and Recognition, ICIAR 2011, held in Burnaby, Canada, in June 2011. The 84 revised full papers presented were carefully reviewed and selected from 147 submissions. The papers are organized in topical sections on image and video processing; feature extraction and pattern recognition; computer vision; color, texture, motion and shape; tracking; biomedical image analysis; biometrics; face recognition; image coding, compression and encryption; and applications.
Author: Alessandro Artusi Publisher: CRC Press ISBN: 1315355337 Category : Computers Languages : en Pages : 174
Book Description
In recent years visual devices have proliferated, from the massive high-resolution, high-contrast screens to the tiny ones on mobile phones, with their limited dynamic range and color gamut. The wide variety of screens on which content may be viewed creates a challenge for developers. Adapting visual content for optimized viewing on all devices is called retargeting. This is the first book to provide a holistic view of the subject, thoroughly reviewing and analyzing the many techniques that have been developed for retargeting along dimensions such as color gamut, dynamic range, and spatial resolution.
Author: Evelyne Lutton Publisher: Springer ISBN: 3319781332 Category : Computers Languages : en Pages : 247
Book Description
This book constitutes the thoroughly refereed post-conference proceedings of the 13th International Conference on Artificial Evolution, EA 2017, held in Paris, France, in October 2017. The 16 revised papers were carefully reviewed and selected from 33 submissions. The papers cover a wide range of topics in the field of artificial evolution, such as evolutionary computation, evolutionary optimization, co-evolution, artificial life, population dynamics, theory, algorithmics and modeling, implementations, application of evolutionary paradigms to the real world (industry, biosciences, ...), other biologically-inspired paradigms (swarm, artificial ants, artificial immune systems, cultural algorithms...), memetic algorithms, multi-objective optimisation, constraint handling, parallel algorithms,, dynamic optimization, machine learning and hybridization with other soft computing techniques.
Author: Kede Ma
Author: Xihe Gao
Author: Hojatollah Yeganeh
Author: Chenwei Deng
Author: Frédéric Dufaux
Author: Hanning Yuan
Author: Dohyoung Lee
Author: Mohamed Kamel
Author: Alessandro Artusi
Author: Evelyne Lutton