Deinterlacing using fuzzy-based motion detection

Ville, Dimitri Van De; Rogge, Boris; Philips, Wilfried; Lemahieu, Ignace

doi:10.1109/kes.1999.820174

Cited by 18 publications

(15 citation statements)

References 9 publications

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“…The algorithm proposed by Van de Ville et al in [15]- [17] describes heuristic knowledge by means of a fuzzy rule set to look for an efficient trade-off between line averaging and field insertion, gradually adapted to the level of motion detected in every pixel. The approach presented by Van de Ville et al will be called Fuzzy Motion Adaptive (FMA) algorithm in this contribution to simplify its citation.…”

Section: Description Of the Starting Algorithmmentioning

confidence: 99%

“…Van de Ville et al described the efficiency of their proposal by de-interlacing several sequences [15]- [17]. After analyzing different values of parameters K, a and b (a and b define the transition zone of the membership functions in Fig.…”

Section: Description Of the Starting Algorithmmentioning

confidence: 99%

“…The universal approximation capability of fuzzy systems has been exploited to interpolate images [12]- [14] and video sequences [15]- [17], [18]- [20]. For deinterlacing purpose, several proposals have been reported in the literature.…”

Section: Introductionmentioning

confidence: 99%

“…Other possible option is to use fuzzy logic and to apply different heuristic rules with approximate levels of uncertainty, which implicitly performs a non-linear filtering [20]. The algorithm in [15]- [17] uses a fuzzy inference rule base to choose de-interlacing strategy according to the detection of motion. More recently, several proposals based on fuzzy techniques have been reported to perform de-interlacing by enhancing edges in the sequence [3]- [7].…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy motion adaptive algorithm and its hardware implementation for video de-interlacing

Gutiérrez-Ríos

Brox

Fernández-Hernández

et al. 2011

Applied Soft Computing

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Interlacing techniques were introduced in the early analog TV transmission systems as an efficient mechanism capable of halving the video bandwidth. Currently, interlacing is also used by some modern digital TV transmission systems, however, there is a problem at the receiver side since the majority of modern display devices require a progressive scanning. De-interlacing algorithms convert an interlaced video signal into a progressive one by performing interpolation. To achieve good de-interlacing results, dynamical and local image features should be considered. The gradual adaptation of the de-interlacing technique as a function of the level of motion detected in each pixel is a powerful method that can be carried out by means of fuzzy inference. The starting point of our study is an algorithm that uses a fuzzy inference system to evaluate motion locally (FMA algorithm). Our approach is based on convolution techniques to process a fuzzy rulebase for motion-adaptive de-interlacing. Different strategies based on bi-dimensional convolution techniques are proposed. In particular, the algorithm called 'single convolution algorithm' introduces significant advantages: a more accurate measurement of the level of motion by using a matrix of weights, and a unique fuzzification process after the global estimation, which reduces the computational cost. Different architectures for the hardware implementation of this algorithm are described in VHDL language. The physical realization is carried out on a RC100 Celoxica FPGA development board.

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Section: Description Of the Starting Algorithmmentioning

confidence: 99%

Section: Description Of the Starting Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fuzzy motion adaptive algorithm and its hardware implementation for video de-interlacing

Gutiérrez-Ríos

Brox

Fernández-Hernández

et al. 2011

Applied Soft Computing

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show abstract

“…Various kinds of motion adaptive (MA) de-interlacing methods [8]- [16] have been proposed to accomplish robust motion detection. Ville [12] proposed a MA technique using a fuzzy motion detector. Sun [13] proposed a shortest path technique of the motion information to re-align the fields of a video image.…”

mentioning

confidence: 99%

Video de-interlacing by adaptive 4-field global/local motion compensated approach

Chang

Lin

Chen

et al. 2005

IEEE Trans. Circuits Syst. Video Technol.

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Abstract-A de-interlacing algorithm using adaptive 4-field global/local motion compensated approach is presented. It consists of block-based directional edge interpolation, same-parity 4-field motion detection, global/local motion estimation and compensation. The edges are sharper when the directional edge interpolation is adopted. The same parity 4-field motion detection and the 4-field local motion estimation detect the static areas and fast motion by four reference fields, and the global motion estimation detects the camera panning and zooming motions. The global and local motion compensation recover the interlaced videos to the progressive ones. Experimental results show that the peak signal-to-noise ratio of our proposed algorithm is 2 3 dB higher than that of previous studies and attain the best quality of subjective view.

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Motion-Compensated Deinterlacing Using Edge Information

Jeong

Lee

2006

Advanced Concepts for Intelligent Vision Systems

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Deinterlacing using fuzzy-based motion detection

Cited by 18 publications

References 9 publications

Fuzzy motion adaptive algorithm and its hardware implementation for video de-interlacing

Fuzzy motion adaptive algorithm and its hardware implementation for video de-interlacing

Video de-interlacing by adaptive 4-field global/local motion compensated approach

Motion-Compensated Deinterlacing Using Edge Information

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