Color shift model-based image enhancement for digital multifocusing based on a multiple color-filter aperture camera

Lee, Eunsung; Kang, Wonseok; Kim, Sangjin; Paik, Joonki

doi:10.1109/tce.2010.5505934

Cited by 22 publications

(12 citation statements)

References 15 publications

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“…To differentiate between the near focus and far focus regions, the concept of dominant region is used as discussed in Section (I). As it can be seen from Figure (1), for the case of the near focus region, σ r is larger than σ g and σ b is the smallest as given in Equation (4). While for the case of the far focus region σ b becomes larger than σ g and σ r the smallest.…”

Section: B Region Mask Creationmentioning

confidence: 79%

“…However depth plane ambiguity remains, as it is assumed that the image lies on one side of focal plane. Also, the range of operation for such scheme is very narrow(1-3 meter) for [4], [5] disparity due to displaced color filters present at the aperture is used as depth cue. However this method is only effective for scenes with certain depth that produces sufficient disparity to account for different levels of depth.…”

Section: Introductionmentioning

confidence: 99%

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Resolving focal plane ambiguity in depth map creation from defocus blur using chromatic aberration

Kumar

Gupta

Venkatesh

2015

2015 10th International Conference on Information, Communications and Signal Processing (ICICS)

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Focal plane ambiguity in depth map creation from defocus blur has remained an challenging problem. In this paper, we present a method to resolve this issue with the help of Chromatic Aberration(CA). CA is a distortion referred to focal length variation of the lens with wavelength of light. When light, a mixture of various monochromatic components, passes through a lens, multiple focal planes are generated due to CA. There also exists an inherent ordering in the defocus blur of the object for different RGB components depending on whether the object lies in the near or far focus region. The ordering reverses as soon as focal planes are crossed. By using this difference in ordering of the defocus amount for different RGB components of an object, we can deduce whether the object is present in front of or behind the image plane, hence using this information, a more reliable depth map can be obtained.

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Section: B Region Mask Creationmentioning

confidence: 79%

Section: Introductionmentioning

confidence: 99%

Resolving focal plane ambiguity in depth map creation from defocus blur using chromatic aberration

Kumar

Gupta

Venkatesh

2015

2015 10th International Conference on Information, Communications and Signal Processing (ICICS)

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“…The proposed imaging system enables a single camera equipped with the MCA to estimate the depth of an object using an appropriate set of image processing algorithms including image segmentation, feature extraction, and registration. In addition to a depth estimation, the proposed MCA camera can be applied to multifocusing [11], image enhancement [12], and simultaneous object tracking and depth estimation [13]. …”

Section: Resultsmentioning

confidence: 99%

Computational Approach to Color Overlapped Integral Imaging for Depth Estimation

Lee¹,

Lim²,

Kim

et al. 2014

IEIE Transactions on Smart Processing and Computing

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Abstract:A computational approach to depth estimations using a color over lapped integral imaging system is presented. The proposed imaging system acquires multiple color images simultaneously through a single lens with an array of multiple pinholes that are distributed around the optical axis. This paper proposes a computational model of the relationship between the real distance of an object and the disparity among different color images. The proposed model can serve as a computational basis of a single camera-based depth estimation.

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“…This portioning process is terminated when the objects of interest in an application are completely isolated. Due to its simplicity and high speed, it is gaining more attraction in different applications, such as the identification of road signs [1], detection of the vacant vehicles in parking spaces [2], classification of the objects of interest in a digital camera image [3], characterization of the microscopic feature of bone for the determination of age at death [4], automatic dental identification system to recognize missing and unidentified persons [5], and face recognition systems, where the clustering technique is applied to extract the required region from an unwanted background region [6,7]. The background region is excluded from further processing and the execution time process can then be reduced [8,9].…”

Section: Introductionmentioning

confidence: 99%

Outlier rejection fuzzy c-means (ORFCM) algorithm for image segmentation

segmentation

2013

Turk J Elec Eng & Comp Sci

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This paper presents a fuzzy clustering-based technique for image segmentation. Many attempts have been put into practice to increase the conventional fuzzy c-means (FCM) performance. In this paper, the sensitivity of the soft membership function of the FCM algorithm to the outlier is considered and the new exponent operator on the Euclidean distance is implemented in the membership function to improve the outlier rejection characteristics of the FCM. The comparative quantitative and qualitative studies are performed among the conventional k-means (KM), moving KM, and FCM algorithms; the latest state-of-the-art clustering algorithms, namely the adaptive fuzzy moving KM , adaptive fuzzy KM, and new weighted FCM algorithms; and the proposed outlier rejection FCM (ORFCM) algorithm. It is revealed from the experimental results that the ORFCM algorithm outperforms the other clustering algorithms in various evaluation functions.

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Color shift model-based image enhancement for digital multifocusing based on a multiple color-filter aperture camera

Cited by 22 publications

References 15 publications

Resolving focal plane ambiguity in depth map creation from defocus blur using chromatic aberration

Resolving focal plane ambiguity in depth map creation from defocus blur using chromatic aberration

Computational Approach to Color Overlapped Integral Imaging for Depth Estimation

Outlier rejection fuzzy c-means (ORFCM) algorithm for image segmentation

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