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Author

Jechang Jeong

Bio: Jechang Jeong is an academic researcher from Hanyang Women's University. The author has contributed to research in topics: Demosaicing & Stairstep interpolation. The author has an hindex of 2, co-authored 5 publications receiving 39 citations.

Papers
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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
30 Jan 2013
TL;DR: The new adaptive interpolation algorithm based on edge direction, which adaptively exploits the advantages of both domains is proposed, which performs well in terms of PSNR and reduces the blocking artifacts.
Abstract: Nowadays, video technology has been successfully improved creating tremendous results. As video technology improve, multimedia devices and demands from users are diversified. Therefore, a video codec used in these devices should support various displays with different resolutions. The technology to generate a higher resolution image from the associated low-resolution image is called interpolation. Interpolation is generally performed in either the spatial domain or the DCT domain. To use the advantages of both domains, we have proposed the new adaptive interpolation algorithm based on edge direction, which adaptively exploits the advantages of both domains. The experimental results demonstrate that our algorithm performs well in terms of PSNR and reduces the blocking artifacts.

2 citations

Journal ArticleDOI
30 Sep 2008
TL;DR: This paper proposes a novel real-time 3D sound representation system for virtual reality, and proposes an enhanced DXF file type that contains the material information and implements the multi-channel sound panning system.
Abstract: 3D sound is of central importance for the virtual reality system, and is becoming increasingly important for the auditory displays and for the human-computer interaction. In this paper, we propose a novel real-time 3D sound representation system for virtual reality. At first, we propose a calculation method of the impulse response for virtual space. To transmit the information of the virtual space, we propose an enhanced DXF file type that contains the material information. And then, we implement the multi-channel sound panning system. we perform the experiment based on computer simulation and prove the utility of the proposed method.

1 citations

25 Aug 2013
TL;DR: This paper proposes merging MPM approach to reduce the bits for signaling and could achieve 0.801% bit reduction while giving similar performance to H.264/AVC while in low bit rate condition.
Abstract: In this paper, we present a method to minimize redundancy of intra-prediction mode. To minimize spatial correlation, H.264/AVC standard utilizes intra-prediction approach, which has nine modes for 4x4, 8x8 blocks, and this mode information should be signaled and four bits are needed to represent nine modes in binary. To minimize the average length of mode information, H.264/AVC estimates Most Probable Mode (MPM) and if the MPM is the same as the best intra-predicted mode, only one bit needs to be signaled. In this paper, we propose merging MPM approach to reduce the bits for signaling. By using adaptive scheme of intra-mode signaling, we could achieve 0.801% bit reduction while giving similar performance. In particular, 1.901% bit reduction was achieved in low bit rate condition. Keywords-H.264/AVC; Intra-prediction; Coding efficiency; most probable mode.
Journal Article
TL;DR: Simulation results proved that the presented high-quality demosaicing technique shows the best image quality performance when compared with several recently presented techniques.
Abstract: Digital cameras adopting a single CCD detector collect image color by subsampling in three color planes and successively interpolating the information to reconstruct full-resolution color images. Therefore, to recovery of a full-resolution color image from a color filter array (CFA) like the Bayer pattern is generally considered as an interpolation issue for the unknown color components. In this paper, we first calculate luminance component value by combining R, G, B channel component information which is quite different from the conventional demosaicing algorithm. Because conventional system calculates G channel component followed by computing R and B channel components. Integrating the obtained gradient edge information and the improved weighting function in luminance component, a new edge sensitive demosaicing technique is presented. Based on 24 well known testing images, simulation results proved that our presented high-quality demosaicing technique shows the best image quality performance when compared with several recently presented techniques.

Cited by
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Journal ArticleDOI
TL;DR: Simulation results verify that, the proposed framework performs better than state-of-the-art demosaicking methods in term of color peak signal-to-noise ratio (CPSNR) and feature similarity index measure (FSIM), as well as higher visual quality.
Abstract: In this letter, we proposed a new framework for color image demosaicking by using different strategies on green (G) and red/blue (R/B) components. Firstly, for G component, the missing samples are estimated by eight-direction weighted interpolation via exploiting spatial and spectral correlations of neighboring pixels. The G plane can be well reconstructed by considering the joint contribution of pre-estimations along eight interpolation directions with different weighting factors. Secondly, we estimate R/B components using guided filter with the reconstructed G plane as guidance image. Simulation results verify that, the proposed framework performs better than state-of-the-art demosaicking methods in term of color peak signal-to-noise ratio (CPSNR) and feature similarity index measure (FSIM), as well as higher visual quality.

36 citations

Journal ArticleDOI
TL;DR: A very low cost edge sensing scheme is proposed, which guides demosaicking by a logistic functional of the difference between directional variations, which achieves substantially higher accuracy and significantly lower cost.
Abstract: Digital cameras that use color filter arrays (CFA) entail a demosaicking procedure to form full RGB images. To digital camera industry, demosaicking speed is as important as demosaicking accuracy, because camera users have been accustomed to viewing captured photos instantly. Moreover, the cost associated with demosaicking should not go beyond the cost saved by using CFA. For this purpose, we revisit the classical Hamilton–Adams (HA) algorithm, which outperforms many sophisticated techniques in both speed and accuracy. Our analysis shows that the HA pipeline is highly efficient to exploit the originally captured data, but its oversimplified inter- and intra-channel smoothness formulation hinder its accuracy. Therefore, we propose a very low cost edge sensing scheme, which guides demosaicking by a logistic functional of the difference between directional variations. We extensively compare our algorithm with 27 demosaicking algorithms by running their open source code on benchmark datasets. Compared with the methods of similar computational cost, our method achieves substantially higher accuracy, whereas compared with the methods of similar accuracy, our method has significantly lower cost. On test images of currently popular resolution, the quality of our algorithm is comparable to top performers, yet our speed is tens of times faster. Source code is submitted to http://ieeexplore.ieee.org .

26 citations

Journal ArticleDOI
TL;DR: Experiments reveal that the proposed pipeline attains excellent visual quality while providing compression performance competitive to that of state-of-the-art compression algorithms for mosaic images.
Abstract: Digital cameras have become ubiquitous for amateur and professional applications. The raw images captured by digital sensors typically take the form of color filter array (CFA) mosaic images, which must be "developed" (via digital signal processing) before they can be viewed. Photographers and scientists often repeat the "development process" using different parameters to obtain images suitable for different purposes. Since the development process is generally not invertible, it is commonly desirable to store the raw (or undeveloped) mosaic images indefinitely. Uncompressed mosaic image file sizes can be more than 30 times larger than those of developed images stored in JPEG format. Thus, data compression is of interest. Several compression methods for mosaic images have been proposed in the literature. However, they all require a custom decompressor followed by development-specific software to generate a displayable image. In this paper, a novel compression pipeline that removes these requirements is proposed. Specifically, mosaic images can be losslessly recovered from the resulting compressed files, and, more significantly, images can be directly viewed (decompressed and developed) using only a JPEG 2000 compliant image viewer. Experiments reveal that the proposed pipeline attains excellent visual quality, while providing compression performance competitive to that of state-of-the-art compression algorithms for mosaic images.

25 citations

Journal ArticleDOI
01 Mar 2018
TL;DR: An improved fuzzy clustering and weighted scheme reconstruction framework that outperforms some state-of-art super-resolution methods in both quantitatively and perceptually.
Abstract: Exploring sparse representation to enhance the resolution of infrared image has attracted much attention in the last decade. However, conventional sparse representation-based super-resolution aim at learning a universal and efficient dictionary pair for image representation. However, considering that a large number of different structures exist in an image, it is insufficient and unreasonable to present various image structures with only one universal dictionary pair. In this paper, we propose an improved fuzzy clustering and weighted scheme reconstruction framework to solve this problem. Firstly, the training patches are divided into multiple clusters by joint learning multiple dictionary pairs with improved fuzzy clustering method. The goal of joint learning is to learn the multiple dictionary pairs which could collectively represent all the training patches with smallest reconstruction error. So that the learned dictionary pairs are more precise and mutually complementary. Then, high-resolution (HR) patches are estimated according to several most accurate dictionary pairs. Finally, these estimated HR patches are integrated together to generate a final HR patch by a weighted scheme. Numerous experiments demonstrate that this framework outperforms some state-of-art super-resolution methods in both quantitatively and perceptually.

24 citations

Journal ArticleDOI
TL;DR: The proposed algorithm uses the channel information from several correlated neighboring pixels to reconstruct the missing color channels of each pixel and has a simple computation structure; therefore, it is appropriate for real-time hardware implementation and can be used in many real- time applications.
Abstract: An efficient edge-based technique for color filter array demosaicking is presented in this paper The proposed algorithm uses the channel information from several correlated neighboring pixels to reconstruct the missing color channels of each pixel We employ a simple edge detector to recognize the edge direction of each processing channel by using directional color differences, and an efficient color interpolator to reconstruct the missing color channels by observing the color correlation and edge information The proposed technique can prevent image blur and demosaicking artefacts; moreover, it has a fixed local window size and requires no previous training and no iterations Extensive experimental results demonstrate that the proposed technique preserves edge features and performs effectively in quantitative evaluations and visual quality The proposed algorithm has a simple computation structure; therefore, it is appropriate for real-time hardware implementation and can be used in many real-time applications

12 citations