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Novel Intra-Field Deinterlacing Algorithm Using Trilateral Filtering Interpolation

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Novel Intra-Field Deinterlacing Algorithm Using Trilateral Filtering Interpolation International Conference on Electronics, Biomedical Engineering and its Applications (ICEBEA'2012) Jan. 7-8, 2012 Dubai Novel Intra-field Deinterlacing Algorithm Using Trilateral Filtering Interpolation Xiangdong Chen and Jechang Jeong The conventional deinterlacing methods interpolate the Abstract—This paper proposes an efficient intra-field missing pixels in two ways: (1) intra-field interpolation, and deinterlacing algorithm using trilateral filtering interpolation method (2) inter-field interpolation. Since inter-field interpolation which has outstanding visual effect. The conventional edge based methods usually use the temporal motion information to deinterlacing algorithms provide unsatisfied image visual effect due estimate the motion statement of objects, and then interpolate to wrongly estimation of edge direction or only taking limited numbers of edge directions into consideration; moreover, In order to pixels along the motion directions. In order to implement make accurate edge estimation, the existing deinterlacing algorithms interpolation properly, accurate motion estimation is essential, try to exhaust all the possible edge directions with setting complex complex motion estimation algorithm is necessary to refine conditions which will unavoidably enhance the computational burden the motion information which need high computational cost, while still producing the pinniform or blur artifacts at edge and especially, when fast and irregular motion exists, it is hard to complex regions. To avoid these problems, the proposed algorithm estimate the motion information or gain wrong motion introduces trilateral filtering interpolation which utilizes the correlation of adjacent 6 pixels by measuring the spatial closeness, information, in this situation, performing deinterlacing with intensity similarity and local gradient among them. Experimental the wrong motion information, artifacts cannot be avoided results show that the proposed algorithm provides satisfied inter-filed interpolation methods also need to use intra-field performances in terms of both objective and subjective image interpolation methods to improve the image quality, so in this qualities. What is more, it just exploits the local spatial similarity paper we focus here on the intra-field interpolation method. among the neighboring pixels without complex preset-conditions Because intra-field deinterlaced methods have a lower which is easier to implement than most of the existing algorithms. computational burden than inter-field methods and it only Keywords—Bilateral filter, Deinterlacing, Edge-preserving, utilizes current frames, these methods are more suitable for Trilateral filter. real-time applications. Many intra-field interpolation methods have been proposed I. INTRODUCTION including line average (LA) and directional spatial interpolations. Edge directional interpolation algorithms such HE international industrial standard for interlaced as ELA (Edge-based LA) [4], EELA (Efficient ELA) [5], scanning technology has been widely applied in various T M-ELA (Modified ELA) [6], these methods interpolate a existing TV broadcasting standards, such as NTSC, PAL, and missing line linearly along the direction between adjacent SECAM. In interlaced scan fields, which contain half samples pixels which has the highest correlation. However, those of original image, that means, only the even or the odd lines of directional interpolation techniques have a low performance a frame, are scanned and displayed sequentially. The goal of due to wrongly estimate the direction or only use limited interlaced scanning is to achieve a tradeoff between frame rate direction models in high spatial frequency regions or and transmission bandwidth requirements [1]. However, due horizontal edge. to the adoption of interlaced scanning, current display systems One of the well-known direction oriented methods is such as HDTV, LCD, and 3DTV, suffer from rebarbative edge-based line average (ELA) [4] algorithm. This method visual artifacts such as interline flicker, line crawling and field considers correlations among neighboring six pixels in upper aliasing. Progressive scanning is preferred because interlacing and low lines around the center pixel to be interpolated, the reduces the vertical display resolution and causes twitter ELA has advantage in that it exhibits high performance with a effects for displaying pictures with high vertical frequency small computational load. However, ELA algorithm has [2]-[3]. Thus, various methods have been presented to reduce artifacts when edge direction is incorrectly estimated. these artifacts in digital display devices. The process to Moreover, ELA suffers from the degradation of the image due convert interlaced fields into progressive frames is called to the limitation of considering candidate edge directions, only de-interlacing. three direction, that is vertical, diagonal and anti-diagonal directions. In order to alleviate the disadvantages of ELA, Xiangdong Chen is with the Department of Electronics & Computer many improved edge-based algorithms, such as efficient ELA Engineering, Hanyang University, Seoul,133-791,Korea (phone: (EELA) [5],modified ELA (MELA) [6], low-complexity +82-2-2220-4370; fax: +82-2-2293-8877; e-mail:[email protected]). Jechang Jeong is now with the Department of Electronics & Computer interpolation method for deinterlacing (LCID) [7], fine Engineering, Hanyang University, Seoul,133-791,Korea (e-mail: directional deinterlacing (FDD)[8] and FDIF deinterlacing [9] [email protected]) 300 International Conference on Electronics, Biomedical Engineering and its Applications (ICEBEA'2012) Jan. 7-8, 2012 Dubai have been proposed. Among these methods, FDIF functions for the spatial and intensity components are defined deinterlacing has outstanding performance since it combinates respectively as 2 adaptive distance weighting scheme with fixed directional s |(x,y) (x0,y0)| W (x, y) = ex p (2) x0,y0 2 2 interpolation filter based on MELA. It utilizes a 6-tap fixed − s coefficients sinc interpolation filter to realize high accurate And σ �− �2 R |I(x,y) I(x0,y0)| interpolation on the edge estimated by MELA, though FDIF W (x, y) = ex p (3) x0,y0 2 2 has high PSNR performance, it still yields jagged artifacts on − R Where I(., .) is the intensity value at the given position. small angle edge because of limited edge directions taken into �− σ � Then, the ensemble weight in the bilateralfilter is the product consideration. Since these algorithms consider more candidate of (2) and (3): edge direction and more accurate edge judgment condition W (x, y) = Ws (x, y)WR (x, y) (4) than ELA, they have better objective or subjective x0,y0 x0,y0 x0,y0 performance than ELA, while they still yields a pinniform-like In practice, each pixel is filtered using normalized weights noise in the complex or texture region and flicker on small as angle edges. To reduce this issue, we apply a trilateral filtering ( 0, 0) ( , ) ( , ) interpolator to interpolate the missing pixel by taking ( , ) ( 0, 0) 0, 0 =̃ (5) closeness among the neighboring pixels and intensity ( , ) ∑ (, ) ( 0,0) 0,0 similarity among them into consideration, and also consider Where ( 0, 0) is the filtered image at location( 0, 0). ∑ the local pixel gradient correlation. Since the local pixel The parameters and are used to adjustthe influence gradient implies the edge information, we do not need to ̃ ofWS and WR, respectively. They can be treated as rough estimate edge directions. The problem we discussed thresholds for identifying pixelssufficiently close or similar to previously can be avoided. The proposed algorithm also has the pixel being filtered.Therefore, compared tothe merits of low complexity and good visual quality. conventional Gaussian filter, the bilateral filter caneffectively The remainder of the paper is organized as follows. The separate the textual and structural information ofthe image. conventional bilateral filter is briefly introduced in section 2. However, even though the bilateral filter is widelyused, no Also, the trilateral filtering method will be introduced in this theoretic manner has been established to determinethe optimal section. The proposed deinterlacing algorithm based on and . Therefore, these parameters aregenerally selected by trilateral filtering interpolation will be explained in Section 3, the empirical method. and the experimental results are presented to evaluate the Bilateral filteringtakes all the neighboring pixels into performance of the proposed method in Section 4. Finally, consideration which have better performance in image conclusions are presented in Section. 5. denoising application, because it make full use of the spatial closeness and intensity similarity of the neighboring pixels, II. CONVENTIONALBILATERAL FILTERAND TRILATERAL however, one of the main limitations of bilateral filtering is FILTER that the range filter coefficients rely heavily on actualpixel A. The Bilateral Filter intensity values, as it does not take into account any regional A bilateral filter is a nonlinear filter that depends on characteristics, which may in turn have beeninfluenced by underlying image data and smoothes images while preserving noise therefore potentially resulting in smoothed texture edges [10]. Bilateral filtering can be regarded as an extended regions and fuzzy boundary when denoising which is proved version of the Gaussian low-pass filtering (smoothing) but in [11]. Motivated by this, we present a novel framework
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