The Experts below are selected from a list of 21300 Experts worldwide ranked by ideXlab platform

Karen Panetta - One of the best experts on this subject based on the ideXlab platform.

  • contrast enhancement for color images using discrete cosine Transform Coefficient scaling
    2016 IEEE Symposium on Technologies for Homeland Security (HST), 2016
    Co-Authors: Arash Samani, Karen Panetta, Sos Agaian
    Abstract:

    For numerous security applications, the timeliness of having quality enhanced images are very critical. Therefore, it is essential to have a low-cost, real-time image enhancement and automatic evaluation tools that can be used be provided across many image based security platforms. In the past, there have been many algorithms proposed to improve image contrast, but most of these algorithms are implemented in the Spatial Domain and very few are designed to work in a Transform Domain. Furthermore, many existing contrast enhancement algorithms only improve the contrast of color images by enhancing the luminance of the image without improving the color content of the image. Besides, many of these methods are tailored to specific image settings. Furthermore, most current state of the art processors used in imaging systems today are equipped with built-in hardware Discrete Cosine Transform or Discrete Fourier Transform modules. In this article, a novel enhancement method to improve image contrast for grayscale and color images is introduced. The proposed method operates in the DCT domain and is computationally efficient, which makes it suitable for realtime imaging systems. Computer simulations demonstrate the efficacy of the proposed approach.

  • Color image enhancement based on the discrete cosine Transform Coefficient histogram
    Journal of Electronic Imaging, 2012
    Co-Authors: Karen Panetta, Junjun Xia, Sos Agaian
    Abstract:

    This paper presents a new technique for contrast enhancement for color images called histogram shifting with alpha rooting. The novelty in the presented method consists in adapting spatial domain techniques into the Transform domain. The benefits of operating in the Transform domain include low complexity of computations, ease of viewing, and manipulation of the frequency composition of the image and preservation of the phase information. The combination of the alpha-rooting algorithm, coupled with histogram shifting shows the method's effectiveness for enhancing overexposed images. The contrast enhancement parameter of the algorithm is established automatically based on the entropy of the images. A comprehensive comparative study on image-enhancement algorithms based on discrete cosine Transform Coefficients is provided. Computer simulations and analysis are provided to compare the enhancement performance of the proposed technique to state of the art approaches. We perform a statistical analysis on the results and quantitatively show that the proposed approach performs well for color image enhancement, which is also validated by ratings from human observers.

  • Image Processing: Algorithms and Systems - Color image enhancement algorithm based on logarithmic Transform Coefficient histogram
    Image Processing: Algorithms and Systems IX, 2011
    Co-Authors: Junjun Xia, Karen Panetta, Sos Agaian
    Abstract:

    This paper presents a new technique for color enhancement based on manipulation of the histogram of logarithmic Transform Coefficients. The proposed technique is simple but more effective than some existing techniques in most case. This method is based on the properties of the histogram of DCT Coefficients, also use the fact that the relationship between stimulus and perception is logarithmic and can afford a marriage between enhancement qualities and computational efficiency. A human visual system-based quantitative measurement of image contrast improvement is also used to determine the optimal parameters for the algorithm. A number of experimental results are presented to illustrate the performance of the proposed algorithm.

  • color image enhancement algorithm based on logarithmic Transform Coefficient histogram
    Proceedings of SPIE, 2011
    Co-Authors: Junjun Xia, Karen Panetta, Sos Agaian
    Abstract:

    This paper presents a new technique for color enhancement based on manipulation of the histogram of logarithmic Transform Coefficients. The proposed technique is simple but more effective than some existing techniques in most case. This method is based on the properties of the histogram of DCT Coefficients, also use the fact that the relationship between stimulus and perception is logarithmic and can afford a marriage between enhancement qualities and computational efficiency. A human visual system-based quantitative measurement of image contrast improvement is also used to determine the optimal parameters for the algorithm. A number of experimental results are presented to illustrate the performance of the proposed algorithm.

  • wavelet Transform Coefficient histogram based image enhancement algorithms
    Proceedings of SPIE, 2010
    Co-Authors: Junjun Xia, Karen Panetta, Sos Agaian
    Abstract:

    This paper proposes two image enhancement algorithms that are based on utilizing histogram data gathered from wavelet Transform domain Coefficients. Computer simulations demonstrate that combining the spatial method of histogram equalization with the logarithmic Transform domain Coefficient histograms achieves a much more balanced enhancement, which outperforms classical histogram equalization algorithms.

Sos Agaian - One of the best experts on this subject based on the ideXlab platform.

  • contrast enhancement for color images using discrete cosine Transform Coefficient scaling
    2016 IEEE Symposium on Technologies for Homeland Security (HST), 2016
    Co-Authors: Arash Samani, Karen Panetta, Sos Agaian
    Abstract:

    For numerous security applications, the timeliness of having quality enhanced images are very critical. Therefore, it is essential to have a low-cost, real-time image enhancement and automatic evaluation tools that can be used be provided across many image based security platforms. In the past, there have been many algorithms proposed to improve image contrast, but most of these algorithms are implemented in the Spatial Domain and very few are designed to work in a Transform Domain. Furthermore, many existing contrast enhancement algorithms only improve the contrast of color images by enhancing the luminance of the image without improving the color content of the image. Besides, many of these methods are tailored to specific image settings. Furthermore, most current state of the art processors used in imaging systems today are equipped with built-in hardware Discrete Cosine Transform or Discrete Fourier Transform modules. In this article, a novel enhancement method to improve image contrast for grayscale and color images is introduced. The proposed method operates in the DCT domain and is computationally efficient, which makes it suitable for realtime imaging systems. Computer simulations demonstrate the efficacy of the proposed approach.

  • Color image enhancement based on the discrete cosine Transform Coefficient histogram
    Journal of Electronic Imaging, 2012
    Co-Authors: Karen Panetta, Junjun Xia, Sos Agaian
    Abstract:

    This paper presents a new technique for contrast enhancement for color images called histogram shifting with alpha rooting. The novelty in the presented method consists in adapting spatial domain techniques into the Transform domain. The benefits of operating in the Transform domain include low complexity of computations, ease of viewing, and manipulation of the frequency composition of the image and preservation of the phase information. The combination of the alpha-rooting algorithm, coupled with histogram shifting shows the method's effectiveness for enhancing overexposed images. The contrast enhancement parameter of the algorithm is established automatically based on the entropy of the images. A comprehensive comparative study on image-enhancement algorithms based on discrete cosine Transform Coefficients is provided. Computer simulations and analysis are provided to compare the enhancement performance of the proposed technique to state of the art approaches. We perform a statistical analysis on the results and quantitatively show that the proposed approach performs well for color image enhancement, which is also validated by ratings from human observers.

  • Image Processing: Algorithms and Systems - Color image enhancement algorithm based on logarithmic Transform Coefficient histogram
    Image Processing: Algorithms and Systems IX, 2011
    Co-Authors: Junjun Xia, Karen Panetta, Sos Agaian
    Abstract:

    This paper presents a new technique for color enhancement based on manipulation of the histogram of logarithmic Transform Coefficients. The proposed technique is simple but more effective than some existing techniques in most case. This method is based on the properties of the histogram of DCT Coefficients, also use the fact that the relationship between stimulus and perception is logarithmic and can afford a marriage between enhancement qualities and computational efficiency. A human visual system-based quantitative measurement of image contrast improvement is also used to determine the optimal parameters for the algorithm. A number of experimental results are presented to illustrate the performance of the proposed algorithm.

  • color image enhancement algorithm based on logarithmic Transform Coefficient histogram
    Proceedings of SPIE, 2011
    Co-Authors: Junjun Xia, Karen Panetta, Sos Agaian
    Abstract:

    This paper presents a new technique for color enhancement based on manipulation of the histogram of logarithmic Transform Coefficients. The proposed technique is simple but more effective than some existing techniques in most case. This method is based on the properties of the histogram of DCT Coefficients, also use the fact that the relationship between stimulus and perception is logarithmic and can afford a marriage between enhancement qualities and computational efficiency. A human visual system-based quantitative measurement of image contrast improvement is also used to determine the optimal parameters for the algorithm. A number of experimental results are presented to illustrate the performance of the proposed algorithm.

  • wavelet Transform Coefficient histogram based image enhancement algorithms
    Proceedings of SPIE, 2010
    Co-Authors: Junjun Xia, Karen Panetta, Sos Agaian
    Abstract:

    This paper proposes two image enhancement algorithms that are based on utilizing histogram data gathered from wavelet Transform domain Coefficients. Computer simulations demonstrate that combining the spatial method of histogram equalization with the logarithmic Transform domain Coefficient histograms achieves a much more balanced enhancement, which outperforms classical histogram equalization algorithms.

B Silver - One of the best experts on this subject based on the ideXlab platform.

  • Transform Coefficient histogram based image enhancement algorithms using contrast entropy
    IEEE Transactions on Image Processing, 2007
    Co-Authors: Sos Agaian, B Silver, Karen Panetta
    Abstract:

    Many applications of histograms for the purposes of image processing are well known. However, applying this process to the Transform domain by way of a Transform Coefficient histogram has not yet been fully explored. This paper proposes three methods of image enhancement: a) logarithmic Transform histogram matching, b) logarithmic Transform histogram shifting, and c) logarithmic Transform histogram shaping using Gaussian distributions. They are based on the properties of the logarithmic Transform domain histogram and histogram equalization. The presented algorithms use the fact that the relationship between stimulus and perception is logarithmic and afford a marriage between enhancement qualities and computational efficiency. A human visual system-based quantitative measurement of image contrast improvement is also defined. This helps choose the best parameters and Transform for each enhancement. A number of experimental results are presented to illustrate the performance of the proposed algorithms

  • logarithmic Transform Coefficient histogram matching with spatial equalization
    Visual Information Processing Conference, 2005
    Co-Authors: B Silver, Sos Agaian, Karen Panetta
    Abstract:

    In this paper we propose an image enhancement algorithm that is based on utilizing histogram data gathered from Transform domain Coefficients that will improve on the limitations of the histogram equalization method. Traditionally, classical histogram equalization has had some problems due to its inherent dynamic range expansion. Many images with data tightly clustered around certain intensity values can be over enhanced by standard histogram equalization, leading to artifacts and overall tonal change of the image. In the Transform domain, one has control over subtle image properties such as low and high frequency content with their respective magnitudes and phases. However, due to the nature of many of these Transforms, the Coefficient’s histograms may be so tightly packed that distinguishing them from one another may be impossible. By placing the Transform Coefficients in the logarithmic Transform domain, it is easy to see the difference between different quality levels of images based upon their logarithmic Transform Coefficient histograms. Our results demonstrate that combing the spatial method of histogram equalization with logarithmic Transform domain Coefficient histograms achieves a much more balanced enhancement, that out performs classical histogram equalization.

  • Visual Information Processing - Logarithmic Transform Coefficient histogram matching with spatial equalization
    Visual Information Processing XIV, 2005
    Co-Authors: B Silver, Sos Agaian, Karen Panetta
    Abstract:

    In this paper we propose an image enhancement algorithm that is based on utilizing histogram data gathered from Transform domain Coefficients that will improve on the limitations of the histogram equalization method. Traditionally, classical histogram equalization has had some problems due to its inherent dynamic range expansion. Many images with data tightly clustered around certain intensity values can be over enhanced by standard histogram equalization, leading to artifacts and overall tonal change of the image. In the Transform domain, one has control over subtle image properties such as low and high frequency content with their respective magnitudes and phases. However, due to the nature of many of these Transforms, the Coefficient’s histograms may be so tightly packed that distinguishing them from one another may be impossible. By placing the Transform Coefficients in the logarithmic Transform domain, it is easy to see the difference between different quality levels of images based upon their logarithmic Transform Coefficient histograms. Our results demonstrate that combing the spatial method of histogram equalization with logarithmic Transform domain Coefficient histograms achieves a much more balanced enhancement, that out performs classical histogram equalization.

  • contrast entropy based image enhancement and logarithmic Transform Coefficient histogram shifting
    International Conference on Acoustics Speech and Signal Processing, 2005
    Co-Authors: B Silver, Sos Agaian, Karen Panetta
    Abstract:

    This paper presents an enhancement technique based upon a new application of histograms on Transform domain Coefficients called logarithmic Transform Coefficient histogram shifting (LTHS). A measure of enhancement based on contrast entropy is used as a tool for evaluating the performance of the proposed enhancement technique and for finding optimal values for variables contained in the enhancement. The algorithm's performance is compared quantitatively to classical histogram equalization using the aforementioned measure of enhancement. Experimental results are presented to show the performance of the proposed algorithm alongside classical histogram equalization.

  • ICASSP (2) - Contrast entropy based image enhancement and logarithmic Transform Coefficient histogram shifting
    Proceedings. (ICASSP '05). IEEE International Conference on Acoustics Speech and Signal Processing 2005., 1
    Co-Authors: B Silver, Sos Agaian, Karen Panetta
    Abstract:

    This paper presents an enhancement technique based upon a new application of histograms on Transform domain Coefficients called logarithmic Transform Coefficient histogram shifting (LTHS). A measure of enhancement based on contrast entropy is used as a tool for evaluating the performance of the proposed enhancement technique and for finding optimal values for variables contained in the enhancement. The algorithm's performance is compared quantitatively to classical histogram equalization using the aforementioned measure of enhancement. Experimental results are presented to show the performance of the proposed algorithm alongside classical histogram equalization.

Thomas Wiegand - One of the best experts on this subject based on the ideXlab platform.

  • improved quantization and Transform Coefficient coding for the emerging versatile video coding vvc standard
    International Conference on Image Processing, 2019
    Co-Authors: Heiko Schwarz, Marta Karczewicz, Thomas Wiegand, Tung Nguyen, Detlev Marpe, Muhammed Zeyd Coban, Jie Dong
    Abstract:

    One key component of all block-based hybrid video codecs is Transform coding of prediction residues, which consists of an orthogonal block Transform, scalar quantization of Transform Coefficients, and entropy coding of the resulting quantization indexes. For improving coding efficiency relative to the state-of-the-art video coding standard HEVC, we propose the following modifications: (1) Replacing scalar quantization with trellis-coded quantization; and (2) utilizing additional statistical dependencies between quantization indexes for entropy coding. The proposed approach was integrated into the first test model VTM-1 for the new standardization project Versatile Video Coding (VVC). Our coding experiments showed average bit-rate savings of 4.9 % for intra-only, 3.4 % for random access, and 2.8 % for low-delay configurations.

  • ICIP - Improved Quantization and Transform Coefficient Coding for the Emerging Versatile Video Coding (VVC) Standard
    2019 IEEE International Conference on Image Processing (ICIP), 2019
    Co-Authors: Heiko Schwarz, Marta Karczewicz, Thomas Wiegand, Tung Nguyen, Detlev Marpe, Muhammed Zeyd Coban, Dong Jie
    Abstract:

    One key component of all block-based hybrid video codecs is Transform coding of prediction residues, which consists of an orthogonal block Transform, scalar quantization of Transform Coefficients, and entropy coding of the resulting quantization indexes. For improving coding efficiency relative to the state-of-the-art video coding standard HEVC, we propose the following modifications: (1) Replacing scalar quantization with trellis-coded quantization; and (2) utilizing additional statistical dependencies between quantization indexes for entropy coding. The proposed approach was integrated into the first test model VTM-1 for the new standardization project Versatile Video Coding (VVC). Our coding experiments showed average bit-rate savings of 4.9 % for intra-only, 3.4 % for random access, and 2.8 % for low-delay configurations.

  • entropy coding of syntax elements related to block structures and Transform Coefficient levels in hevc
    Proceedings of SPIE, 2012
    Co-Authors: Tung Nguyen, Heiko Schwarz, Philipp Helle, Martin Winken, Detlev Marpe, Thomas Wiegand
    Abstract:

    The most recent video compression technology is High Efficiency Video Coding (HEVC). This soon to be completed standard is a joint development by Video Coding Experts Group (VCEG) of ITU-T and Moving Picture Experts Group (MPEG) of ISO/IEC. As one of its major technical novelties, HEVC supports variable prediction and Transform block sizes using the quadtree approach for block partitioning. In terms of entropy coding, the Draft International Standard (DIS) of HEVC specifies context-based adaptive binary arithmetic coding (CABAC) as the single mode of operation. In this paper, a description of the specific CABAC-based entropy coding part in HEVC is given that is related to block structures and Transform Coefficient levels. In addition, experimental results are presented that indicate the benefit of the Transform-Coefficient level coding design in HEVC in terms of improved coding performance and reduced complexity.

  • reduced complexity entropy coding of Transform Coefficient levels using truncated golomb rice codes in video compression
    International Conference on Image Processing, 2011
    Co-Authors: Tung Nguyen, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
    Abstract:

    In hybrid video coding, the difference between the intra or inter prediction signal and the original signal is transmitted using block-based Transform coding. The state-of-the-art in coding the quantized Transform Coefficients is the approach specified in H.264/AVC for context-adaptive binary arithmetic coding. It has, however, been shown that the number of binary symbols that have to be arithmetically coded for the Transform Coefficients can become very large, making the concept less attractive for high rate applications. To overcome this issue, we propose a combination of simple variable-length codes and context-adaptive binary coding, which yields the same coding efficiency as the H.264/AVC Transform Coefficient coding at a lower complexity level and which has been adopted into the HEVC test model (HM).

  • ICIP - Reduced-complexity entropy coding of Transform Coefficient levels using truncated golomb-rice codes in video compression
    2011 18th IEEE International Conference on Image Processing, 2011
    Co-Authors: Tung Nguyen, Heiko Schwarz, Detlev Marpe, Thomas Wiegand
    Abstract:

    In hybrid video coding, the difference between the intra or inter prediction signal and the original signal is transmitted using block-based Transform coding. The state-of-the-art in coding the quantized Transform Coefficients is the approach specified in H.264/AVC for context-adaptive binary arithmetic coding. It has, however, been shown that the number of binary symbols that have to be arithmetically coded for the Transform Coefficients can become very large, making the concept less attractive for high rate applications. To overcome this issue, we propose a combination of simple variable-length codes and context-adaptive binary coding, which yields the same coding efficiency as the H.264/AVC Transform Coefficient coding at a lower complexity level and which has been adopted into the HEVC test model (HM).

Pierre Duhamel - One of the best experts on this subject based on the ideXlab platform.

  • Transform Coefficient Coding for Screen Content in Versatile Video Coding (VVC)
    2019
    Co-Authors: Mohsen Abdoli, Félix Henry, Patrice Brault, Frédéric Dufaux, Pierre Duhamel
    Abstract:

    A Transform Coefficient coding scheme is proposed for 4 × 4 blocks in Versatile Video Coding (VVC), targeting screen content applications. The proposed algorithm, called Unary Bitplane Coding (UBC), uses unary codes of the Coefficient amplitudes and represents each block by their bitplanes. This representation allows exploiting further contextual information for source separation during the entropy coding. Experiments in the Joint Exploration test Model (JEM) show that replacing the existing Transform coding with UBC only for 4 × 4 blocks brings on average 2.8% and 3.4% BD-R gain in the random access and all intra modes, respectively.

  • ICASSP - Transform Coefficient Coding for Screen Content in Versatile Video Coding (VVC)
    ICASSP 2019 - 2019 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2019
    Co-Authors: Mohsen Abdoli, Félix Henry, Patrice Brault, Frédéric Dufaux, Pierre Duhamel
    Abstract:

    A Transform Coefficient coding scheme is proposed for 4 × 4 blocks in Versatile Video Coding (VVC), targeting screen content applications. The proposed algorithm, called Unary Bitplane Coding (UBC), uses unary codes of the Coefficient amplitudes and represents each block by their bitplanes. This representation allows exploiting further contextual information for source separation during the entropy coding. Experiments in the Joint Exploration test Model (JEM) show that replacing the existing Transform coding with UBC only for 4 × 4 blocks brings on average 2.8% and 3.4% BD-R gain in the random access and all intra modes, respectively.