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Author

Xiangdong Chen

Other affiliations: Hanyang University
Bio: Xiangdong Chen is an academic researcher from Nanjing University of Posts and Telecommunications. The author has contributed to research in topics: Demosaicing & Stairstep interpolation. The author has an hindex of 6, co-authored 14 publications receiving 167 citations. Previous affiliations of Xiangdong Chen include Hanyang University.

Papers
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Journal ArticleDOI
TL;DR: A novel color image demosaicking algorithm using a voting-based edge direction detection method and a directional weighted interpolation method that provides superior performance in terms of both objective and subjective image qualities is presented.
Abstract: In this paper, we present a novel color image demosaicking algorithm using a voting-based edge direction detection method and a directional weighted interpolation method. By introducing the voting strategy, the interpolation direction of the center missing color component can be determined accurately. Along the determined interpolation direction, the center missing color component is interpolated using the gradient weighted interpolation method by exploring the intra-channel gradient correlation of the neighboring pixels. As compared with the latest demosaicking algorithms, experiments show that the proposed algorithm provides superior performance in terms of both objective and subjective image qualities.

50 citations

Journal ArticleDOI
TL;DR: Zhang et al. as mentioned in this paper proposed a multidirectional weighted interpolation algorithm for color filter array interpolation, which exploits to greater degree correlations among neighboring pixels along eight directions to improve the interpolation performance.
Abstract: This paper presents a novel multidirectional weighted interpolation algorithm for color filter array interpolation. Our proposed method has two contributions to demosaicking. First, different from conventional interpolation methods based on two directions or four directions, the proposed method exploits to greater degree correlations among neighboring pixels along eight directions to improve the interpolation performance. Second, we propose an efficient postprocessing method to reduce interpolation artifacts based on the color difference planes. Compared with conventional state-of-the-art demosaicking algorithms, our experimental results show the proposed algorithm provides superior performance in both objective and subjective image quality. Furthermore, this implementation has moderate computational complexity.

43 citations

01 Jan 2015
TL;DR: This paper presents a novel multidirectional weighted interpolation algorithm for color filter array interpolation that exploits to greater degree correlations among neighboring pixels along eight directions to improve the interpolation performance.
Abstract: This paper presents a novel multidirectional weighted interpolation algorithm for color filter array inter- polation. Our proposed method has two contributions to demosaicking. First, different from conventional interpolation methods based on two directions or four directions, the proposed method exploits to greater degree correlations among neighboring pixels along eight directions to improve the interpolation perfor- mance. Second, we propose an efficient postprocessing method to reduce interpolation artifacts based on the color difference planes. Compared with conventional state-of-the-art demosaick- ing algorithms, our experimental results show the proposed algorithm provides superior performance in both objective and subjective image quality. Furthermore, this implementation has moderate computational complexity.

38 citations

Journal ArticleDOI
TL;DR: An efficient intra-field deinterlacing algorithm which implements a filter switching interpolation method (FSID) according to different local region features, which produces outstanding visual results.
Abstract: This paper proposes an efficient intra-field deinterlacing algorithm which implements a filter switching interpolation method (FSID) according to different local region features, which produces outstanding visual results In this method, a bilateral filter is used for smooth regions to interpolate the missing line due to its accurate interpolation performance through use of the closeness and similarity among the neighboring pixels On the other hand, a trilateral filter is used for complex regions to interpolate the missing line since it has high edge-preserving ability due to taking into accountthe closeness and similarity among neighboring pixels, but also the pixel gradient Experimental results show that the proposed FSID algorithm provides satisfactory performances in terms of both objective and subjective image quality In addition, the algorithm exploits the local spatial similarity among the neighboring pixels without complex preset-conditions, which is easier to implement than many other existing algorithms

18 citations


Cited by
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Journal ArticleDOI
TL;DR: This paper introduces a new demosaicking algorithm based on polynomial interpolation-based demosaicks, and shows how the predictors can be combined according to the proposed edge classifier.
Abstract: Demosaicking is a digital image process to reconstruct full color digital images from incomplete color samples from an image sensor. It is an unavoidable process for many devices incorporating camera sensor (e.g., mobile phones, tablet, and so on). In this paper, we introduce a new demosaicking algorithm based on polynomial interpolation-based demosaicking. Our method makes three contributions: calculation of error predictors, edge classification based on color differences, and a refinement stage using a weighted sum strategy. Our new predictors are generated on the basis of on the polynomial interpolation, and can be used as a sound alternative to other predictors obtained by bilinear or Laplacian interpolation. In this paper, we show how our predictors can be combined according to the proposed edge classifier. After populating three color channels, a refinement stage is applied to enhance the image quality and reduce demosaicking artifacts. Our experimental results show that the proposed method substantially improves over the existing demosaicking methods in terms of objective performance (CPSNR, S-CIELAB $\Delta E^{\ast }$ , and FSIM), and visual performance.

55 citations

Journal ArticleDOI
TL;DR: Zhang et al. as mentioned in this paper proposed a multidirectional weighted interpolation algorithm for color filter array interpolation, which exploits to greater degree correlations among neighboring pixels along eight directions to improve the interpolation performance.
Abstract: This paper presents a novel multidirectional weighted interpolation algorithm for color filter array interpolation. Our proposed method has two contributions to demosaicking. First, different from conventional interpolation methods based on two directions or four directions, the proposed method exploits to greater degree correlations among neighboring pixels along eight directions to improve the interpolation performance. Second, we propose an efficient postprocessing method to reduce interpolation artifacts based on the color difference planes. Compared with conventional state-of-the-art demosaicking algorithms, our experimental results show the proposed algorithm provides superior performance in both objective and subjective image quality. Furthermore, this implementation has moderate computational complexity.

43 citations

01 Jan 2015
TL;DR: This paper presents a novel multidirectional weighted interpolation algorithm for color filter array interpolation that exploits to greater degree correlations among neighboring pixels along eight directions to improve the interpolation performance.
Abstract: This paper presents a novel multidirectional weighted interpolation algorithm for color filter array inter- polation. Our proposed method has two contributions to demosaicking. First, different from conventional interpolation methods based on two directions or four directions, the proposed method exploits to greater degree correlations among neighboring pixels along eight directions to improve the interpolation perfor- mance. Second, we propose an efficient postprocessing method to reduce interpolation artifacts based on the color difference planes. Compared with conventional state-of-the-art demosaick- ing algorithms, our experimental results show the proposed algorithm provides superior performance in both objective and subjective image quality. Furthermore, this implementation has moderate computational complexity.

38 citations

Journal ArticleDOI
TL;DR: A four-direction residual interpolation (FDRI) method for color filter array interpolation that provides a superior performance in terms of objective and subjective quality compared with the conventional state-of-the-art demosaicking methods.
Abstract: In this paper, we propose a four-direction residual interpolation (FDRI) method for color filter array interpolation. The proposed algorithm exploits a guided filtering process to generate the tentative image. The residual image is generated by exploiting the tentative and original images. We use an FDRI algorithm to more accurately estimate the missing pixel values; the estimated image is adaptively combined with a joint inverse gradient weight. Based on the experimental results, the proposed method provides a superior performance in terms of objective and subjective quality compared with the conventional state-of-the-art demosaicking methods.

37 citations