Motion adaptive interpolation with horizontal motion detection for deinterlacing

Lin, Shyh-Feng; Chang, Yu‐Ling; Chen, Liang-Gee

doi:10.1109/tce.2003.1261227

Cited by 82 publications

(4 citation statements)

References 21 publications

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“…For our application, however, the presence of high frequency interlacing artifacts [17, 18] precludes the direct use of these techniques. When the scene motion is fast relative to the frame capture rate in interlaced video, a combing effect arises [19].…”

Section: Frame Selectionmentioning

confidence: 99%

Enhanced video indirect ophthalmoscopy (VIO) via robust mosaicing

Estrada¹,

Tomasi²,

Cabrera³

et al. 2011

Biomed. Opt. Express

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Indirect ophthalmoscopy (IO) is the standard of care for evaluation of the neonatal retina. When recorded on video from a head-mounted camera, IO images have low quality and narrow Field of View (FOV). We present an image fusion methodology for converting a video IO recording into a single, high quality, wide-FOV mosaic that seamlessly blends the best frames in the video. To this end, we have developed fast and robust algorithms for automatic evaluation of video quality, artifact detection and removal, vessel mapping, registration, and multi-frame image fusion. Our experiments show the effectiveness of the proposed methods.

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Section: Frame Selectionmentioning

confidence: 99%

Enhanced video indirect ophthalmoscopy (VIO) via robust mosaicing

Estrada¹,

Tomasi²,

Cabrera³

et al. 2011

Biomed. Opt. Express

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“…However, it's unable to detect horizontal motion and sensitive to video noise. In [8], a five directional temporal interpolation is applied to detect horizontal motion, and a morphological operation is proposed to reduce noise. In [9], a median filter in 5-field motion detection is proposed to detect motion more accurate.…”

Section: -Field Extended Gaussian Filtering Motion Detectionmentioning

confidence: 99%

“…In [6], ELA is enhanced with two useful measurements to alleviate the misleading decisions. In [8], ELA is modified as an ELA-median interpolation with horizontal motion detection to make the edge sharper. In [7], ELA is extended to three dimensions and combined with texture detection to fit various areas.…”

Section: Aw-elamentioning

confidence: 99%

An Efficient Motion Adaptive De-interlacing and Its VLSI Architecture Design

Sun

Zheng

et al. 2008

2008 IEEE Computer Society Annual Symposium on VLSI

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This paper presents an efficient motion adaptive deinterlacing technique that consists of two main steps, i.e. 4-field extended Gaussian filtering motion detection and adjustable window ELA de-interlacing. Four consecutive interlaced fields are used to detect motion accurately. With a Gaussian filter, the motion detection can eliminate the influence of noise. An adjustable window ELA de-interlacing is adopt to process motion pixels, which can reconstruct image with high quality even in areas with horizontal edge and texture. Experimental results show that the proposed algorithm outperforms previous methods both objectively and subjectively. Based on our method, the high speed VLSI architecture has been designed and implemented. The operating frequency of the chip is 126MHz that it could process format conversion in real-time for both SDTV and HDTV applications.

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“…To enhance recording image speed and reduce the channel bandwidth of the system, an interlaced scanning camera is adopted. The video scanning mode is separated into interlaced scanning and progressive scanning [32,33]. One of two single-field images (even field and odd field) is firstly recorded in the interlaced scanning, after a field-cycle time, secondly the other is recorded, and finally the two field images are compounded into a frame image.…”

Section: Introductionmentioning

confidence: 99%

3D shape measurement for moving scenes using an interlaced scanning colour camera

Cao¹,

Cao²,

Lu³

et al. 2014

J. Opt.

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A Fourier transform deinterlacing algorithm (FTDA) is proposed to eliminate the blurring and dislocation of the fringe patterns on a moving object captured by an interlaced scanning colour camera in phase measuring profilometry (PMP). Every frame greyscale fringe from three colour channels of every colour fringe is divided into even and odd field fringes respectively, each of which is respectively processed by FTDA. All of the six frames deinterlaced fringes from one colour fringe form two sets of three-step phase-shifted greyscale fringes, with which two 3D shapes corresponding to two different moments are reconstructed by PMP within a frame period. The deinterlaced fringe is identical with the exact frame fringe at the same moment theoretically. The simulation and experiments show its feasibility and validity. The method doubles the time resolution, maintains the precision of the traditional phase measurement profilometry, and has potential applications in the moving and online object’s 3D shape measurements.

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Motion adaptive interpolation with horizontal motion detection for deinterlacing

Abstract: Abstract

Cited by 82 publications

References 21 publications

Enhanced video indirect ophthalmoscopy (VIO) via robust mosaicing

Enhanced video indirect ophthalmoscopy (VIO) via robust mosaicing

An Efficient Motion Adaptive De-interlacing and Its VLSI Architecture Design

3D shape measurement for moving scenes using an interlaced scanning colour camera

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