The Experts below are selected from a list of 153 Experts worldwide ranked by ideXlab platform

Zhou Wang - One of the best experts on this subject based on the ideXlab platform.

  • high dynamic range Image compression by optimizing tone Mapped Image quality index
    IEEE Transactions on Image Processing, 2015
    Co-Authors: Hojatollah Yeganeh, Kai Zeng, Zhou Wang
    Abstract:

    Tone mapping operators (TMOs) aim to compress high dynamic range (HDR) Images to low dynamic range (LDR) ones so as to visualize HDR Images on standard displays. Most existing TMOs were demonstrated on specific examples without being thoroughly evaluated using well-designed and subject-validated Image quality assessment models. A recently proposed tone Mapped Image quality index (TMQI) made one of the first attempts on objective quality assessment of tone Mapped Images. Here, we propose a substantially different approach to design TMO. Instead of using any predefined systematic computational structure for tone mapping (such as analytic Image transformations and/or explicit contrast/edge enhancement), we directly navigate in the space of all Images, searching for the Image that optimizes an improved TMQI. In particular, we first improve the two building blocks in TMQI—structural fidelity and statistical naturalness components—leading to a TMQI-II metric. We then propose an iterative algorithm that alternatively improves the structural fidelity and statistical naturalness of the resulting Image. Numerical and subjective experiments demonstrate that the proposed algorithm consistently produces better quality tone Mapped Images even when the initial Images of the iteration are created by the most competitive TMOs. Meanwhile, these results also validate the superiority of TMQI-II over TMQI. 1 1 Partial preliminary results of this work were presented at ICASSP 2013 and ICME 2014.

  • High dynamic range Image tone mapping by optimizing tone Mapped Image quality index
    2014 IEEE International Conference on Multimedia and Expo (ICME), 2014
    Co-Authors: Hojatollah Yeganeh, Kai Zeng, Zhou Wang
    Abstract:

    An active research topic in recent years is to design tone mapping operators (TMOs) that convert high dynamic range (H-DR) to low dynamic range (LDR) Images, so that HDR Images can be visualized on standard displays. Nevertheless, most existing work has been done in the absence of a well-established and subject-validated Image quality assessment (IQA) model, without which fair comparisons and further improvement are difficult. Recently, a tone Mapped Image quality index (TMQI) was proposed, which has shown to have good correlation with subjective evaluations of tone Mapped Images. Here we propose a substantially different approach to design TMO, 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 Images, searching for the Image that optimizes TMQI. The navigation involves an iterative process that alternately improves the structural fidelity and statistical naturalness of the resulting Image, which are the two fundamental building blocks in TMQI. Experiments demonstrate the superior performance of the proposed method.

  • objective quality assessment of tone Mapped Images
    IEEE Transactions on Image Processing, 2013
    Co-Authors: Hojatollah Yeganeh, Zhou Wang
    Abstract:

    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. Different TMOs create different tone-Mapped Images, and a natural question is which one has the best quality. Without an appropriate quality measure, different TMOs cannot be compared, and further improvement is directionless. Subjective rating may be a reliable evaluation method, but it is expensive and time consuming, and more importantly, is difficult to be embedded into optimization frameworks. Here we propose an objective quality assessment algorithm for tone-Mapped Images by combining: 1) a multiscale signal fidelity measure on the basis of a modified structural similarity index and 2) a naturalness measure on the basis of intensity statistics of natural Images. Validations using independent subject-rated Image databases show good correlations between subjective ranking score and the proposed tone-Mapped Image quality index (TMQI). Furthermore, we demonstrate the extended applications of TMQI using two examples - parameter tuning for TMOs and adaptive fusion of multiple tone-Mapped Images.

Hojatollah Yeganeh - One of the best experts on this subject based on the ideXlab platform.

  • high dynamic range Image compression by optimizing tone Mapped Image quality index
    IEEE Transactions on Image Processing, 2015
    Co-Authors: Hojatollah Yeganeh, Kai Zeng, Zhou Wang
    Abstract:

    Tone mapping operators (TMOs) aim to compress high dynamic range (HDR) Images to low dynamic range (LDR) ones so as to visualize HDR Images on standard displays. Most existing TMOs were demonstrated on specific examples without being thoroughly evaluated using well-designed and subject-validated Image quality assessment models. A recently proposed tone Mapped Image quality index (TMQI) made one of the first attempts on objective quality assessment of tone Mapped Images. Here, we propose a substantially different approach to design TMO. Instead of using any predefined systematic computational structure for tone mapping (such as analytic Image transformations and/or explicit contrast/edge enhancement), we directly navigate in the space of all Images, searching for the Image that optimizes an improved TMQI. In particular, we first improve the two building blocks in TMQI—structural fidelity and statistical naturalness components—leading to a TMQI-II metric. We then propose an iterative algorithm that alternatively improves the structural fidelity and statistical naturalness of the resulting Image. Numerical and subjective experiments demonstrate that the proposed algorithm consistently produces better quality tone Mapped Images even when the initial Images of the iteration are created by the most competitive TMOs. Meanwhile, these results also validate the superiority of TMQI-II over TMQI. 1 1 Partial preliminary results of this work were presented at ICASSP 2013 and ICME 2014.

  • High dynamic range Image tone mapping by optimizing tone Mapped Image quality index
    2014 IEEE International Conference on Multimedia and Expo (ICME), 2014
    Co-Authors: Hojatollah Yeganeh, Kai Zeng, Zhou Wang
    Abstract:

    An active research topic in recent years is to design tone mapping operators (TMOs) that convert high dynamic range (H-DR) to low dynamic range (LDR) Images, so that HDR Images can be visualized on standard displays. Nevertheless, most existing work has been done in the absence of a well-established and subject-validated Image quality assessment (IQA) model, without which fair comparisons and further improvement are difficult. Recently, a tone Mapped Image quality index (TMQI) was proposed, which has shown to have good correlation with subjective evaluations of tone Mapped Images. Here we propose a substantially different approach to design TMO, 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 Images, searching for the Image that optimizes TMQI. The navigation involves an iterative process that alternately improves the structural fidelity and statistical naturalness of the resulting Image, which are the two fundamental building blocks in TMQI. Experiments demonstrate the superior performance of the proposed method.

  • objective quality assessment of tone Mapped Images
    IEEE Transactions on Image Processing, 2013
    Co-Authors: Hojatollah Yeganeh, Zhou Wang
    Abstract:

    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. Different TMOs create different tone-Mapped Images, and a natural question is which one has the best quality. Without an appropriate quality measure, different TMOs cannot be compared, and further improvement is directionless. Subjective rating may be a reliable evaluation method, but it is expensive and time consuming, and more importantly, is difficult to be embedded into optimization frameworks. Here we propose an objective quality assessment algorithm for tone-Mapped Images by combining: 1) a multiscale signal fidelity measure on the basis of a modified structural similarity index and 2) a naturalness measure on the basis of intensity statistics of natural Images. Validations using independent subject-rated Image databases show good correlations between subjective ranking score and the proposed tone-Mapped Image quality index (TMQI). Furthermore, we demonstrate the extended applications of TMQI using two examples - parameter tuning for TMOs and adaptive fusion of multiple tone-Mapped Images.

Gangyi Jiang - One of the best experts on this subject based on the ideXlab platform.

  • blind tone Mapped Image quality assessment with Image segmentation and visual perception
    Journal of Visual Communication and Image Representation, 2020
    Co-Authors: Biwei Chi, Gangyi Jiang, Zongju Peng, Fen Chen
    Abstract:

    Abstract With tone mapping, high dynamic range (HDR) Image contents can be displayed on low dynamic range (LDR) display devices, in which some important visual information may be distorted. Thus, the tone Mapped Image (TMI) quality assessment is one of important issues in HDR Image/video processing fields. Considering the difference of visual distortion degrees between the flat and complex regions in TMI, and considering that high-quality TMI should preserve as much information as possible of its original HDR Image especially in the high/low luminance regions, this paper proposes a new blind TMI quality assessment method with Image segmentation and visual perception. First, we design different features to describe the distortion of TMI’s different regions with two kinds of TMI segmentation. Then, considering that there lacks an efficient algorithm to quantify the importance of features, a feature clustering scheme is designed to eliminate the poor effect feature components in the extracted features to improve the effectiveness of the selected features. Finally, considering the diversity of tone mapping operator (TMO), which may cause global and local distortion of TMI, some other global features are also combined. At last, a final feature vector is formed to synthetically describe the distortion in TMI and used to blindly predict the TMI’s quality. Experimental results in the public ESPL-LIVE HDR database show that the Pearson linear correlation coefficient and Spearman rank order correlation coefficient of the proposed method reach 0.8302 and 0.7887, respectively, which is superior to the state-of-the-art blind TMI quality assessment methods, and it means that the proposed method is highly consistent with human visual perception.

  • blind tone Mapped Image quality assessment based on clustering perception
    Fifth Conference on Frontiers in Optical Imaging Technology and Applications, 2018
    Co-Authors: Hao Jiang, Gangyi Jiang
    Abstract:

    In order to display a high dynamic range (HDR) Image on a standard monitor, tone-mapping operators (TMOs) aim to compress HDR Images into low dynamic range tone-Mapped (TM) Images. To accurately evaluate the performance of different TMOs, this paper proposes a no-reference Image quality assessment (IQA) method for TM Images. Firstly, the Image is divided into dark area, middle area and bright area by using clustering algorithm. The entropy and area ratio features are extracted from three areas mentioned above and the saliency area that is detected by the proposed method. Then the natural scene statistics features of the luminance channel and RGB color channels of TMI are used to assess the luminance naturalness and chrominance naturalness, respectively. Finally the support vector regression module is utilized to yield a quality score of the TM Images. The experimental results on the tone-Mapped Image database (TMID) show the effectiveness of the proposed algorithm. Compared with the existing representative IQA methods, the proposed method has better performance.

  • blind tone Mapped Image quality assessment based on brightest darkest regions naturalness and aesthetics
    IEEE Access, 2018
    Co-Authors: Gangyi Jiang, Hao Song, Yang Song, Zongju Peng
    Abstract:

    A tone-Mapped Image (TMI) converted from its high-dynamic-range Image (HDRI) tends to appear overexposed in its brightest regions or underexposed in its darkest regions, resulting in inevitable loss of details and impaired naturalness and aesthetics. To address this issue, this paper proposes a novel blind TMI quality assessment (BTMIQA) method for HDRIs used in different dynamic range displays. The brightest and darkest regions of the TMI are first defined and segmented, and their local detail features are used in combination with the global detail feature of the TMI to evaluate the detail distortion. The natural scene statistics features of the luminance and yellow channels of the TMI are then used to evaluate the luminance naturalness and chrominance naturalness, respectively. Subsequently, to predict the aesthetics of the TMI, a series of colorfulness features are extracted and concatenated in a final feature vector, which is used to evaluate the TMI quality by random forest regression. Experiments are performed on the TMI database and ESPL-LIVE high-dynamic-range database, and the results show the effectiveness of the proposed method. Compared with the existing TMI quality assessment methods, the proposed BTMIQA method is more consistent with human visual perception.

  • a new tone Mapped Image quality assessment approach for high dynamic range imaging system
    International Conference on Image Processing, 2017
    Co-Authors: Yang Song, Gangyi Jiang, Hao Jiang, Feng Shao, Zongju Peng
    Abstract:

    Tone-mapping operators are designed to apply high dynamic range (HDR) Images on widely-used low dynamic range (LDR) devices. Developing well-performed tone-Mapped Image quality assessment (IQA) method is highly desired because traditional IQA method cannot be adopted in cross dynamic range quality measuring. To this end, we proposed a quality assessment method based on Image exposure property. Specifically, an Image exposure property determination model is utilized to segment HDR Image into different exposure region. Then, quality features are extracted according to the distortion characteristics of each exposure region. Finally, the quality of tone-Mapped Image can be acquired by a trained regression model. Validation experiments on public database show that the proposed method can accurately predict the quality of tone-Mapped Image.

  • naturalness index for a tone Mapped high dynamic range Image
    Applied Optics, 2016
    Co-Authors: Yang Song, Gangyi Jiang, Feng Shao, Yun Zhang, Zongju Peng
    Abstract:

    High dynamic range (HDR) Images can only be backward-compatible with existing low dynamic range (LDR) imaging systems after being processed by tone-mapping operators. Hence, the quality assessment (QA) of tone-Mapped HDR Images has become an important and challenging issue in HDR imaging research. In this paper, we propose a naturalness index for a tone-Mapped Image to predict its quality. First, we extract the statistical features of the tone-Mapped Image's luminance value and use it to evaluate the brightness naturalness with no reference information. Meanwhile, we use perceptive color, Image contrast, and detail information to represent the Image content and predict their naturalness qualities, respectively. Then, the four components of the naturalness qualities are combined to yield the overall naturalness quality of the tone-Mapped Image. Experimental results on a publicly available database demonstrated that, in comparison with a traditional LDR Image QA method and a leading tone-Mapped Image QA method, the proposed method has better performance in evaluating a tone-Mapped Image's quality.

Zongju Peng - One of the best experts on this subject based on the ideXlab platform.

  • blind tone Mapped Image quality assessment based on regional sparse response and aesthetics
    Entropy, 2020
    Co-Authors: Fen Chen, Zongju Peng, Yang Song
    Abstract:

    High dynamic range (HDR) Images give a strong disposition to capture all parts of natural scene information due to their wider brightness range than traditional low dynamic range (LDR) Images. However, to visualize HDR Images on common LDR displays, tone mapping operations (TMOs) are extra required, which inevitably lead to visual quality degradation, especially in the bright and dark regions. To evaluate the performance of different TMOs accurately, this paper proposes a blind tone-Mapped Image quality assessment method based on regional sparse response and aesthetics (RSRA-BTMI) by considering the influences of detail information and color on the human visual system. Specifically, for the detail loss in a tone-Mapped Image (TMI), multi-dictionaries are first designed for different brightness regions and whole TMI. Then regional sparse atoms aggregated by local entropy and global reconstruction residuals are presented to characterize the regional and global detail distortion in TMI, respectively. Besides, a few efficient aesthetic features are extracted to measure the color unnaturalness of TMI. Finally, all extracted features are linked with relevant subjective scores to conduct quality regression via random forest. Experimental results on the ESPL-LIVE HDR database demonstrate that the proposed RSRA-BTMI method is superior to the existing state-of-the-art blind TMI quality assessment methods.

  • blind tone Mapped Image quality assessment with Image segmentation and visual perception
    Journal of Visual Communication and Image Representation, 2020
    Co-Authors: Biwei Chi, Gangyi Jiang, Zongju Peng, Fen Chen
    Abstract:

    Abstract With tone mapping, high dynamic range (HDR) Image contents can be displayed on low dynamic range (LDR) display devices, in which some important visual information may be distorted. Thus, the tone Mapped Image (TMI) quality assessment is one of important issues in HDR Image/video processing fields. Considering the difference of visual distortion degrees between the flat and complex regions in TMI, and considering that high-quality TMI should preserve as much information as possible of its original HDR Image especially in the high/low luminance regions, this paper proposes a new blind TMI quality assessment method with Image segmentation and visual perception. First, we design different features to describe the distortion of TMI’s different regions with two kinds of TMI segmentation. Then, considering that there lacks an efficient algorithm to quantify the importance of features, a feature clustering scheme is designed to eliminate the poor effect feature components in the extracted features to improve the effectiveness of the selected features. Finally, considering the diversity of tone mapping operator (TMO), which may cause global and local distortion of TMI, some other global features are also combined. At last, a final feature vector is formed to synthetically describe the distortion in TMI and used to blindly predict the TMI’s quality. Experimental results in the public ESPL-LIVE HDR database show that the Pearson linear correlation coefficient and Spearman rank order correlation coefficient of the proposed method reach 0.8302 and 0.7887, respectively, which is superior to the state-of-the-art blind TMI quality assessment methods, and it means that the proposed method is highly consistent with human visual perception.

  • blind tone Mapped Image quality assessment based on brightest darkest regions naturalness and aesthetics
    IEEE Access, 2018
    Co-Authors: Gangyi Jiang, Hao Song, Yang Song, Zongju Peng
    Abstract:

    A tone-Mapped Image (TMI) converted from its high-dynamic-range Image (HDRI) tends to appear overexposed in its brightest regions or underexposed in its darkest regions, resulting in inevitable loss of details and impaired naturalness and aesthetics. To address this issue, this paper proposes a novel blind TMI quality assessment (BTMIQA) method for HDRIs used in different dynamic range displays. The brightest and darkest regions of the TMI are first defined and segmented, and their local detail features are used in combination with the global detail feature of the TMI to evaluate the detail distortion. The natural scene statistics features of the luminance and yellow channels of the TMI are then used to evaluate the luminance naturalness and chrominance naturalness, respectively. Subsequently, to predict the aesthetics of the TMI, a series of colorfulness features are extracted and concatenated in a final feature vector, which is used to evaluate the TMI quality by random forest regression. Experiments are performed on the TMI database and ESPL-LIVE high-dynamic-range database, and the results show the effectiveness of the proposed method. Compared with the existing TMI quality assessment methods, the proposed BTMIQA method is more consistent with human visual perception.

  • a new tone Mapped Image quality assessment approach for high dynamic range imaging system
    International Conference on Image Processing, 2017
    Co-Authors: Yang Song, Gangyi Jiang, Hao Jiang, Feng Shao, Zongju Peng
    Abstract:

    Tone-mapping operators are designed to apply high dynamic range (HDR) Images on widely-used low dynamic range (LDR) devices. Developing well-performed tone-Mapped Image quality assessment (IQA) method is highly desired because traditional IQA method cannot be adopted in cross dynamic range quality measuring. To this end, we proposed a quality assessment method based on Image exposure property. Specifically, an Image exposure property determination model is utilized to segment HDR Image into different exposure region. Then, quality features are extracted according to the distortion characteristics of each exposure region. Finally, the quality of tone-Mapped Image can be acquired by a trained regression model. Validation experiments on public database show that the proposed method can accurately predict the quality of tone-Mapped Image.

  • naturalness index for a tone Mapped high dynamic range Image
    Applied Optics, 2016
    Co-Authors: Yang Song, Gangyi Jiang, Feng Shao, Yun Zhang, Zongju Peng
    Abstract:

    High dynamic range (HDR) Images can only be backward-compatible with existing low dynamic range (LDR) imaging systems after being processed by tone-mapping operators. Hence, the quality assessment (QA) of tone-Mapped HDR Images has become an important and challenging issue in HDR imaging research. In this paper, we propose a naturalness index for a tone-Mapped Image to predict its quality. First, we extract the statistical features of the tone-Mapped Image's luminance value and use it to evaluate the brightness naturalness with no reference information. Meanwhile, we use perceptive color, Image contrast, and detail information to represent the Image content and predict their naturalness qualities, respectively. Then, the four components of the naturalness qualities are combined to yield the overall naturalness quality of the tone-Mapped Image. Experimental results on a publicly available database demonstrated that, in comparison with a traditional LDR Image QA method and a leading tone-Mapped Image QA method, the proposed method has better performance in evaluating a tone-Mapped Image's quality.

Mohammed Yeasin - One of the best experts on this subject based on the ideXlab platform.

  • optical flow in log Mapped Image plane
    International Workshop on Robot Vision, 2001
    Co-Authors: Mohammed Yeasin
    Abstract:

    In this article we propose a novel approach to compute the optical flow directly on log-Mapped Images. We propose the use of a generalized dynamic Image model (GDIM) based method for computing the optical flow as opposed to the brightness constancy model (BCM) based method. We introduce a new notion of “variable window” and use the space-variant form of gradient operator while computing the spatiotemporal gradient in log-Mapped Images for a better accuracy and to ensure that the local neighborhood is preserved. We emphasize that the proposed method must be numerically accurate, provides a consistent interpretation and is capable of computing the peripheral motion. Experimental results on both the synthetic and real Images have been presented to show the efficacy of the proposed method.

  • optical flow in log Mapped Image plane a new approach
    Lecture Notes in Computer Science, 2001
    Co-Authors: Mohammed Yeasin
    Abstract:

    In this article we propose a novel approach to compute the optical flow directly on log-Mapped Images. We propose the use of a generalized dynamic Image model (GDIM) based method for computing the optical flow as opposed to the brightness constancy model (BCM) based method. We introduce a new notion of "variable window" and use the space-variant form of gradient operator while computing the spatio-temporal gradient in log-Mapped Images for a better accuracy and to ensure that the local neighborhood is preserved. We emphasize that the proposed method must be numerically accurate, provides a consistent interpretation and is capable of computing the peripheral motion. Experimental results on both the synthetic and real Images have been presented to show the efficacy of the proposed method.