The Experts below are selected from a list of 267 Experts worldwide ranked by ideXlab platform
Yuk-hee Chan - One of the best experts on this subject based on the ideXlab platform.
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Restoration of half-toned color-Quantized Images using Particle Swarm Optimization with wavelet mutation
TENCON 2008 - 2008 IEEE Region 10 Conference, 2008Co-Authors: C.w. Yeung, Yuk-hee Chan, Sai Ho Ling, Frank H. F. LeungAbstract:Restoration of color-Quantized Images is rarely addressed in the literature, especially when the Images are color-Quantized with halftoning. Most existing restoration algorithms are generally inadequate to deal with this problem as they were proposed for restoring noisy blurred Images. In this paper, a restoration algorithm based on particle swarm optimization with wavelet mutation (WPSO) is proposed to solve the problem. This algorithm makes a good use of the available color palette and the mechanism of a halftoning process to derive useful a priori information for restoration. Simulation results show that it can improve the quality of a half-toned color-Quantized Image remarkably in terms of both SNRI and convergence rate. The subjective quality of the restored Images can also be improved.
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A simulated annealing restoration algorithm for restoring halftoned color-Quantized Images
Signal Processing: Image Communication, 2006Co-Authors: Yik-hing Fung, Yuk-hee ChanAbstract:Restoration of color-Quantized Images is rarely addressed in the literature especially when the Images are color-Quantized with halftoning. Most existing restoration algorithms are generally inadequate to deal with this problem as they were proposed for restoring noisy blurred Images. In this paper, a restoration algorithm based on simulated annealing is proposed to solve the problem. This algorithm makes a good use of the available color palette and the mechanism of a halftoning process to derive useful a priori information for restoration. Simulation results show that it can improve the quality of a halftoned color-Quantized Image remarkably in terms of both SNR and CIELAB color difference metric. The subjective quality of the restored Images can also be improved.
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A POCS-based restoration algorithm for restoring halftoned color-Quantized Images
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, 2006Co-Authors: Yik-hing Fung, Yuk-hee ChanAbstract:This paper studies the restoration of Images which are color-Quantized with error diffusion. Though there are many reported algorithms proposed for restoring noisy blurred color Images and inverse halftoning, restoration of color-Quantized Images is rarely addressed in the literature especially when the Images are color-Quantized with halftoning. Direct application of existing restoration techniques are generally inadequate to deal with this problem. In this paper, a restoration algorithm based on projection onto convex sets is proposed. This algorithm makes use of the available color palette and the mechanism of a halftoning process to derive useful a priori information for restoration. Simulation results showed that it could improve the quality of a halftoned color-Quantized Image remarkably in terms of both SNR and CIELAB color difference metric.
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A regularized constrained iterative restoration algorithm for restoring color-Quantized Images
Signal Processing, 2005Co-Authors: Yuk-hee Chan, Yik-hing FungAbstract:This paper studies the restoration of color-Quantized Images. Restoration of color-Quantized Images is rarely addressed in literature, and direct applications of existing restoration techniques are generally inadequate to deal with this problem. In this paper, we propose a restoration algorithm for restoring color-Quantized Images. This algorithm makes good use of the available color palette to derive useful a priori information for restoration. Simulation results show that it can improve the quality of a color-Quantized Image remarkably in terms of both SNR and CIELAB color difference metric. Its performance is obviously better than that of other conventional algorithms in the simulation.
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EUSIPCO - Regularized restoration of color Quantized Images
2002Co-Authors: Yuk-hee Chan, Yik-hing FungAbstract:This paper studies the restoration of color Quantized Images. Restoration of color Quantized Images is rarely addressed in the literature, and direct applications of existing restoration techniques are generally inadequate to deal with this problem. We propose a restoration algorithm specific to color Quantized Images, which makes a good use of the available color palette to derive useful a priori information for restoration. The proposed restoration algorithm is shown to be able to improve the quality of a color Quantized Image to a certain extent.
Yik-hing Fung - One of the best experts on this subject based on the ideXlab platform.
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A POCS-based restoration algorithm for restoring halftoned color-Quantized Images
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, 2006Co-Authors: Yik-hing Fung, Yuk-hee ChanAbstract:This paper studies the restoration of Images which are color-Quantized with error diffusion. Though there are many reported algorithms proposed for restoring noisy blurred color Images and inverse halftoning, restoration of color-Quantized Images is rarely addressed in the literature especially when the Images are color-Quantized with halftoning. Direct application of existing restoration techniques are generally inadequate to deal with this problem. In this paper, a restoration algorithm based on projection onto convex sets is proposed. This algorithm makes use of the available color palette and the mechanism of a halftoning process to derive useful a priori information for restoration. Simulation results showed that it could improve the quality of a halftoned color-Quantized Image remarkably in terms of both SNR and CIELAB color difference metric.
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A simulated annealing restoration algorithm for restoring halftoned color-Quantized Images
Signal Processing: Image Communication, 2006Co-Authors: Yik-hing Fung, Yuk-hee ChanAbstract:Restoration of color-Quantized Images is rarely addressed in the literature especially when the Images are color-Quantized with halftoning. Most existing restoration algorithms are generally inadequate to deal with this problem as they were proposed for restoring noisy blurred Images. In this paper, a restoration algorithm based on simulated annealing is proposed to solve the problem. This algorithm makes a good use of the available color palette and the mechanism of a halftoning process to derive useful a priori information for restoration. Simulation results show that it can improve the quality of a halftoned color-Quantized Image remarkably in terms of both SNR and CIELAB color difference metric. The subjective quality of the restored Images can also be improved.
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A regularized constrained iterative restoration algorithm for restoring color-Quantized Images
Signal Processing, 2005Co-Authors: Yuk-hee Chan, Yik-hing FungAbstract:This paper studies the restoration of color-Quantized Images. Restoration of color-Quantized Images is rarely addressed in literature, and direct applications of existing restoration techniques are generally inadequate to deal with this problem. In this paper, we propose a restoration algorithm for restoring color-Quantized Images. This algorithm makes good use of the available color palette to derive useful a priori information for restoration. Simulation results show that it can improve the quality of a color-Quantized Image remarkably in terms of both SNR and CIELAB color difference metric. Its performance is obviously better than that of other conventional algorithms in the simulation.
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EUSIPCO - Regularized restoration of color Quantized Images
2002Co-Authors: Yuk-hee Chan, Yik-hing FungAbstract:This paper studies the restoration of color Quantized Images. Restoration of color Quantized Images is rarely addressed in the literature, and direct applications of existing restoration techniques are generally inadequate to deal with this problem. We propose a restoration algorithm specific to color Quantized Images, which makes a good use of the available color palette to derive useful a priori information for restoration. The proposed restoration algorithm is shown to be able to improve the quality of a color Quantized Image to a certain extent.
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An iterative algorithm for restorating color-Quantized Images
2002Co-Authors: Yik-hing Fung, Yuk-hee ChanAbstract:This paper studies the restoration of color-Quantized Images. Restoration of color-Quantized Images is rarely addressed in the literature, and direct applications of existing restoration techniques are generally inadequate to deal with this problem. We propose a POCS-based restoration algorithm specific to color-Quantized Images, which makes a good use of the available color palette to derive useful a priori information for restoration. The proposed restoration algorithm is shown to he capable of improving the quality of an color-Quantized Image to
Anders Garpebring - One of the best experts on this subject based on the ideXlab platform.
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haralick texture features from apparent diffusion coefficient adc mri Images depend on imaging and pre processing parameters
Scientific Reports, 2017Co-Authors: Patrik Brynolfsson, David Nilsson, Turid Torheim, Thomas Asklund, Camilla Thellenberg Karlsson, Johan Trygg, Tufve Nyholm, Anders GarpebringAbstract:In recent years, texture analysis of medical Images has become increasingly popular in studies investigating diagnosis, classification and treatment response assessment of cancerous disease. Despite numerous applications in oncology and medical imaging in general, there is no consensus regarding texture analysis workflow, or reporting of parameter settings crucial for replication of results. The aim of this study was to assess how sensitive Haralick texture features of apparent diffusion coefficient (ADC) MR Images are to changes in five parameters related to Image acquisition and pre-processing: noise, resolution, how the ADC map is constructed, the choice of quantization method, and the number of gray levels in the Quantized Image. We found that noise, resolution, choice of quantization method and the number of gray levels in the Quantized Images had a significant influence on most texture features, and that the effect size varied between different features. Different methods for constructing the ADC maps did not have an impact on any texture feature. Based on our results, we recommend using Images with similar resolutions and noise levels, using one quantization method, and the same number of gray levels in all Quantized Images, to make meaningful comparisons of texture feature results between different subjects.
Christian Roux - One of the best experts on this subject based on the ideXlab platform.
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Transmission errors recovery using fuzzy block similitary measures
1997Co-Authors: Basel Solaiman, Ramesh Pyndiah, Omar Aitsab, Christian RouxAbstract:In addition to the source coding artifacts, the encoded bit streams representing codeword indexes of a vector Quantized Image are vulnerable to transmission or media impairments. Impulse block noise in the received Images is the main artifact due to transmission errors. We use the fuzzy set theory to represent the vague concept of a block similarity with its spatial context. This approach is conducted in order to detect and to conceal the transmission errors. Error concealment by searching the best matching codeword is an attractive alternative to the commonly used interpolation approach. It reduces considerably the computational complexity at the receiver end. Simulation results show that the proposed method considerably improves the subjective quality of VQ Images transmitted over noisy channels.
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Transmission errors recovery of Quantized Images using fuzzy block similarity measures
IEEE Transactions on Image Processing, 1997Co-Authors: Basel Solaiman, Ramesh Pyndiah, Christian RouxAbstract:In addition to the source coding artifacts, the encoded bit streams representing codeword indexes of a vector Quantized Image are vulnerable to transmission or media impairments. Impulse block noise in the received Images is the main artifact due to transmission errors. We use the fuzzy set theory to represent the vague concept of a block similarity with its spatial context. This approach is conducted in order to detect and to conceal the transmission errors. Error concealment by searching the best matching codeword is an attractive alternative to the commonly used interpolation approach. It reduces considerably the computational complexity at the receiver end. Simulation results show that the proposed method considerably improves the subjective quality of VQ Images transmitted over noisy channels.
Basel Solaiman - One of the best experts on this subject based on the ideXlab platform.
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Transmission errors recovery using fuzzy block similitary measures
1997Co-Authors: Basel Solaiman, Ramesh Pyndiah, Omar Aitsab, Christian RouxAbstract:In addition to the source coding artifacts, the encoded bit streams representing codeword indexes of a vector Quantized Image are vulnerable to transmission or media impairments. Impulse block noise in the received Images is the main artifact due to transmission errors. We use the fuzzy set theory to represent the vague concept of a block similarity with its spatial context. This approach is conducted in order to detect and to conceal the transmission errors. Error concealment by searching the best matching codeword is an attractive alternative to the commonly used interpolation approach. It reduces considerably the computational complexity at the receiver end. Simulation results show that the proposed method considerably improves the subjective quality of VQ Images transmitted over noisy channels.
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Transmission errors recovery of Quantized Images using fuzzy block similarity measures
IEEE Transactions on Image Processing, 1997Co-Authors: Basel Solaiman, Ramesh Pyndiah, Christian RouxAbstract:In addition to the source coding artifacts, the encoded bit streams representing codeword indexes of a vector Quantized Image are vulnerable to transmission or media impairments. Impulse block noise in the received Images is the main artifact due to transmission errors. We use the fuzzy set theory to represent the vague concept of a block similarity with its spatial context. This approach is conducted in order to detect and to conceal the transmission errors. Error concealment by searching the best matching codeword is an attractive alternative to the commonly used interpolation approach. It reduces considerably the computational complexity at the receiver end. Simulation results show that the proposed method considerably improves the subjective quality of VQ Images transmitted over noisy channels.
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joint optimization of multi dimensional sofm codebooks with qam modulations for vector Quantized Image transmission
Proceedings IWISP '96#R##N#4–7 November 1996 Manchester United Kingdom, 1996Co-Authors: O Aitsab, Ramesh Pyndiah, Basel SolaimanAbstract:Publisher Summary The requirements of digital transmission systems are now becoming so severe that it is no longer possible to optimize different functions in the system independently. Powerful source coding techniques are used to increase the number of sources transmitted in a given frequency bandwidth. However, the quality of the transmitted sources using these source coding techniques usually depends on the channel bit error rate. To go one step further, one would expect the subjective quality of the transmitted sources to remain acceptable even at a very low channel signal to noise ratio as in an analogue transmission system. Traditionally, source coding and channel modulation characteristics are optimized separately. Source coding reduces the redundancy in an input signal, while the modulation adapts the information to the transmission channel characteristics to be noise resistant. In this chapter, the internal structure of the source coding scheme is trained in conjunction with a QAM modulation type to increase the tolerance of transmission error effects. Results obtained using the standard Lenna Images are extremely encouraging.
