Deinterlacing

Abstract: A digital image enhancer includes a deinterlacing processor receptive to an interlaced video stream. The deinterlacing processor includes a first deinterlacer and a second deinterlacer and provides a deinterlaced video stream. The digital image enhancer also includes a video output processor receptive to the output of the deinterlaced video stream to provide a scaled, deinterlaced video stream. A portable DVD player including the digital video enhancer has a generally thin prismatic enclosure having a first major surface, a second major surface separated from said first major surface, and side surfaces connecting the first major surface to the second major surface. At least a portion of the first major surface includes a video display, and the enclosure includes a DVD entry port such that a DVD can be inserted into the enclosure.

Abstract: In this paper, we propose a new deinterlacing algorithm, which is an edge dependent interpolation (EDI) algorithm based on a horizontal edge pattern. Generally, a conventional EDI algorithm has a visually better performance than any other deinterlacing algorithms using one field. However, it produces unpleasant results due to the failure of estimating edge direction. In order to exactly detect edge direction, we use not only simple difference but also edge patterns. Experimental results indicate that the proposed algorithm outperforms conventional approaches with respect to both objective and subjective criteria.

Abstract: Method and apparatus are disclosed for deinterlacing of an interlaced video frame sequence using interpolation estimations, such as spatial and temporal interpolations. Interpolations requiring a less accurate estimation of missing pixel values in the frames being deinterlaced, such that an interpolation may be performed with a minimum of error, are performed before interpolations which require a more accurate estimation of missing pixel values for performing an interpolation, such that estimates of missing pixel values are obtained with a minimum of error. Interpolation estimations are weighted in combination for computing approximations of missing pixel values in accordance with the errors associated with the respective interpolations.

Abstract: We present a new method for the motion detection/compensation between opposite parity fields in interlaced video sequences. We introduce a phase-correction filter, which is applied to one type (even or odd) of fields before motion detection/compensation. By means of this phase-correction filter, the motion-compensated PSNR has been improved by more than 2 dB, on average. We also present a new deinterlacing algorithm based on the newly developed motion detection/compensation. This algorithm requires storing one field only, and the phase-corrected field is used for both motion detection/compensation and intrafield deinterlacing, thus making the proposed algorithm computationally very efficient. Excellent deinterlacing results have been obtained.