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检索条件"机构=Image Processing and Intelligent System Laboratory Graduate School of Advanced Imaging Science"

共 81 条记录，以下是51-60 订阅

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Single camera-based full depth map estimation using color shifting property of a multiple color-filter aperture

Single camera-based full depth map estimation using color sh...

引用

International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Seungwon Lee Junghyun Lee Monson H. Hayes Aggelos K. Katsaggelos Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea Department of Electrical Engineering and Computer Science Northwestern University Evanston IL USA

A multiple color-filter aperture (MCA) camera can provide depth information as well as color and intensity in the single-camera framework, where the MCA generates misalignment between color channels depending on the distance of a region-of-interest. In this paper, we present a single camera-based estimation of the full depth map using the color shifting property of the MCA. For estimating the color shifting vectors (CSVs) among red, green, and blue color channels, edges are extracted at each color channel. At the edge, we estimate CSVs using normalized cross correlation combined with color shifting mask map. A full depth map is then generated by depth interpolation using the matting Laplacian method from sparsely estimated CSVs at an edge location. Experimental results show that the proposed method can not only estimate the full depth map but also correct the misaligned color image to generate photorealistic color images using a single camera equipped with MCA.

关键词： image color analysis Cameras Estimation Channel estimation image edge detection Interpolation Apertures

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REGULARIZED ADAPTIVE SUPER-RESOLUTION USING KERNEL ESTIMATION-BASED EDGE RECONNECTION AND KERNEL ORIENTATION CONSTRAINTS

REGULARIZED ADAPTIVE SUPER-RESOLUTION USING KERNEL ESTIMATIO...

引用

IEEE International Conference on image processing

作者： Jaehwan Jeon Jinhee Lee Eunsung Lee Monson H. Hayes Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University (CAU) Seoul South Korea 1st Research and Development Center/CP group Nextchip Company Limited Seoul South Korea

This paper presents a spatially adaptive super-resolution (SR) algorithm using homogeneous region analysis for minimizing undesired interpolation artifacts such as aliasing and jagged edges. The proposed regularized SR algorithm incorporates two constraints enforcing (i) disconnected edges to be reconnected and (ii) orientation-adaptive regularization. By combining two constraints in the regularization framework, the proposed SR algorithm can significantly reduce aliasing artifacts and, as a result, produce edge-preserved high-resolution (HR) images. In addition to the formulation of the regularized SR algorithm with hybrid constraints, experimental results show that the proposed SR algorithm improves peak-to-peak signal-to-noise ratio (PSNR) of the reconstructed HR images by up to 5[dB]over existing state-of-the-art SR methods.

关键词： image edge detection Kernel image reconstruction Estimation Filtering algorithms Maximum likelihood detection image resolution

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Peripheral region enhancement of geometrically compensated images from a fisheye lens

Peripheral region enhancement of geometrically compensated i...

引用

1st IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2011

作者： Kim, Donggyun Kim, Seonyung Paik, Joonki Jung, Junghoon Kim, Taechan Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea Republic of System LSI Samsung Electronics Co. Ltd. Suwon Korea Republic of

ISBN: (纸本)9781457702341

In this paper, we propose a peripheral region enhancement method for geometrically compensated images from a fisheye lens. The proposed method provides a novel filtering method based on the degradation model of a fisheye lens. More specifically, we first present a space-variant image degradation model using generic Gaussian function with geometric distortion. We then apply the truncated constraint least squares (TCLS) filter for restoring the peripheral region of the image in the real-time, space-adaptive manner. Experimental results demonstrate that the proposed method can enhance the peripheral region while keeping the high-quality center region. © 2011 IEEE.

关键词： image enhancement

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Geometrical transformation-based ghost artifacts removing for high dynamic range image

Geometrical transformation-based ghost artifacts removing fo...

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IEEE International Conference on image processing

作者： Jaehyun Im Sangsik Jang Seungwon Lee Joonki Paik Image Processing and Intelligent System Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University South Korea

In this paper, we propose a ghost artifacts removing algorithm for obtaining artifact-free high dynamic range (HDR) images in the presence of camera movement. Existing HDR methods work on condition that there is no camera movement when acquiring multiple low dynamic range (LDR) images. For overcoming such unrealistic restriction, the proposed algorithm first specifies the target and the source images in the set of acquired LDR images, and then the source image is transformed to fit the target image by estimating translation and rotation components in the affine matrix. Therefore, the proposed algorithm can reconstruct the HDR image without ghost artifacts because camera movement is completely removed in transformed images. Experimental results show that the proposed algorithm successfully removes ghost artifacts. For this reason, the proposed algorithm can extend application areas of HDR imaging to various mobile imaging devices, such as a handheld camcorder and a mobile phone camera.

关键词： Cameras Dynamic range Heuristic algorithms image processing Erbium Software

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SIMULTANEOUS OBJECT TRACKING AND DEPTH ESTIMATION USING COLOR SHIFTING PROPERTY OF A MULTIPLE COLOR-FILTER APERTURE CAMERA

SIMULTANEOUS OBJECT TRACKING AND DEPTH ESTIMATION USING COLO...

引用

IEEE International Conference on Acoustics, Speech and Signal processing

作者： Seungwon Lee Jinhee Lee Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging ScienceMultimedia and Film Chung-Ang University Seoul Korea

ISBN: (纸本)9781457705380

A multiple color-filter aperture (MCA) camera can provide depth information as well as color and intensity in the single-camera framework, where the MCA generates misalignment between color channels depending on the distance of a region-of-interest. In this paper, we present a simultaneous object tracking and depth estimation approach based on the color shifting property of an MCA camera. An object region is first extracted by using Markov Chain Monte Carlo (MCMC) sampling-based particle filter. The extracted object's region has color misalignment among RGB planes depending on the distance of the object. We estimate color shifting vectors (CSVs) between green-and-red (G-R) and green-and-blue (G-B) channels using a simplified elastic registration algorithm. Using the color shifting property of the MCA camera, the depth of the object's region is estimated from CSVs. From experimental results, we can show the MCA camera-based surveillance system can estimate depth information as well as track object.

关键词： Video surveillance particle filters image registration image color analysis image motion analysis tracking objects system buses compensatory amounts Maximum credible accidents color cast Cameras Misalignment Color SURVEILLANCE systemS

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Vaguelette-wavelet decomposition for real-time image restoration using directional wavelet bases

Vaguelette-wavelet decomposition for real-time image restora...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Wonseok Kang Eunsung Lee Sangjin Kim Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea

Conventional image restoration filters, such as Wiener filter, often exhibit either noise amplification or over-smoothing problem. On the other hand, advanced image restoration techniques, such as iterative regularization or combined Fourier and wavelet domain thresholding techniques, is not suitable for real-time application because of high computational overhead. For overcoming these problems, we adopt vaguelette-wavelet decomposition (VWD) approach to realtime, space-frequency adaptive image restoration based on the estimated point spread-function (PSF) and directional wavelet bases.

关键词： image restoration Wavelet transforms Low pass filters Filtering algorithms Real time systems Noise

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Wavelet-based enhancement of color image using combined local variance and entropy analysis

Wavelet-based enhancement of color image using combined loca...

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2010 International Conference on Consumer Electronics, ICCE 2010

作者： Jun, Sinyoung Lee, Eunsung Kim, Sangjin Paik, Joonki Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea Republic of

ISBN: (纸本)9781424443161

This paper presents a novel wavelet-based image enhancement approach to reduce noise in a single-sensor color camera. Most traditional noise reduction methods tend to over-suppress high-frequency details. For overcoming this problem we first decompose the input image into flat and edge regions, and adaptively remove noise by multiplying alpha map and wavelet transform coefficients of LH, HL, and HH bands. After removing noise in the flat region, we further remove noise in edge regions by adaptive shrink of wavelet coefficients based on the entropy. Experimental result show the proposed algorithm is proved to be able to reduce noise without losing sharp details and is suitable for commercial low-cost such as digital cameras, CCTV, and surveillance systems. ©2010 IEEE.

关键词： image enhancement

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image restoration using alpha map-based fusion for multiple color aperture computational camera

Image restoration using alpha map-based fusion for multiple ...

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2010 International Conference on Consumer Electronics, ICCE 2010

作者： Lee, Eunsung Maik, Vivek Jun, Sinyoung Kim, Sangjin Paik, Joonki Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea Republic of

ISBN: (纸本)9781424443161

We present a novel image restoration approach by fusing multiple images acquired by a multiple color aperture computational camera for overcoming the limit of conventional image restoration algorithms, such as high computational load and post-processing artifacts. The proposed restoration framework utilizes color matching, alignment, and fusion of multiple images acquired by using multiple color apertures. The alpha map-based image fusion step successfully restores high-frequency components of meaningful edge regions. The proposed scheme can achieve automatic focusing and varying depth of filed at low cost for low-end consumer cameras. ©2010 IEEE.

关键词： Color

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Wavelet-based enhancement of color image using combined local variance and entropy analysis

Wavelet-based enhancement of color image using combined loca...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Sinyoung Jun Eunsung Lee Sangjin Kim Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea

ISBN: (纸本)9781424443147

关键词： Wavelet analysis Entropy Analysis of variance image analysis image color analysis Noise reduction Colored noise image enhancement Cameras Wavelet transforms

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image restoration using alpha map-based fusion for multiple color aperture computational camera

Image restoration using alpha map-based fusion for multiple ...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Eunsung Lee Vivek Maik Sinyoung Jun Sangjin Kim Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea

ISBN: (纸本)9781424443147;9781424443161

关键词： image restoration Apertures Focusing Signal processing algorithms Color image fusion Smart cameras Costs Digital images Educational technology

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