domain transcoding from MPEG-2 to H.264 is studied. In [10], an algorithm is developed to perform transcoding with This paper discusses the problem of transcoding between spatial resolution downscaling from MPEG-2 to VC-1. In VC-1 and H.264 video standards. VC-1 uses an adaptive[7], a pixel domain transcoding algorithm from VC-1 to block size integer transform, which is different from the 4x4 H.264 is presented. There are several works that address the integer transform used by H.264. We propose an algorithm fundamental problem of converting MPEG discrete cosine to transcode the transform coefficients from VC-1 to those transform (DCT) coefficients to H.264 coefficients entirely for H.264, which is a fundamental step for transform in the transform domain by using matrix multiplication [1, 3, domain transcoding. The paper also presents a fast 4]. In this paper, we focus on the problem of transcoding computation version of the algorithm. The implementation VC-1 to H.264 in the transform domain and an algorithm to of the proposed algorithm shows that the quality of the perform this operation is developed. The proposed design is video remains roughly the same while the complexity is implemented for P frames and compared to a full cascade greatly reduced when compared with the reference full pixel domain transcoder. The rest of the paper is organized cascade pixel domain transcoder.as follows: Section II presents an algorithm for VC-1 to H.264 transcoding. In Section III a fast implementation for Index Terms -Video Coding, Visual Communications, the algorithm proposed in Section II is described. And in Transcoding, H.264, VC-1, Transform domain Section IV the implementation and results of the previous algorithm are presented.

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In transcoding, quantization and other techniques could result in lower video output quality. To address this problem a novel super-resolution (SR) algorithm based on irregular sampling (IS) is presented in this paper. The highresolution (HR) frame is obtained as an interpolation of one or more previous frames; the resulting interpolated frame has samples non-uniformly spaced in the areas where movement happened. To reconstruct the irregular sampled frame we use a well-known irregular sampling algorithm modified to perform in 2-D space. Moreover, because SR algorithms are in general computationally expensive, we also present a hardware feasibility study. The proposed solution does not target any specific application but we have specifically tested the algorithm in a transcoding environment. In particular, we have applied it to VC-1 to H.264 transcoding and applied down/up sampling. Experimental results show that the proposed algorithm improves video quality significantly.

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