In this paper, we propose two novel approaches for the error concealment used in H.264 codec. The first one is a direction-oriented candidate set, which decides a proper candidate set of motion vectors by using the trend of collocated motion vector. The second is a predicted boundary matching criterion, which uses one-order prediction of pixel value on boundary to reduce the incurred error of traditional boundary matching criterion. Compared with the bidirectional motion vector refinement (BMVR), the proposed approaches can elevate about 0.75 dB of peak-signal to noise ratio (PSNR) value and perform well especially for the video sequences with moderate and fast motion.

Motion estimation plays a key role in a motion-compensated block-based hybrid DCT coding scheme. To speed up the computation of motion estimation, many fast search algorithms have been proposed. A recent one, called enhanced hexagon-based search (EHEXBS), focused on reducing the number of search points in a fine-resolution inner search after a low-resolution hexagonal search. In this paper, we propose a novel inner search algorithm, named efficient hexagonal inner search (EHIS), to further reduce the number of search points. In EHIS, we use the central minimal distortion information and exploit the distortion information of the points located on the hexagonal pattern. Experimental results show that EHIS performs better than the EHEXBS in terms of the number of search points or the mean squared error. In addition, EHIS omits the overhead of six additions in each EHEXBS.

The set partitioning in hierarchical trees (SPIHT) algorithm is a computationally simple and efficient zerotree coding technique for image compression. However, the high working memory requirement is its main drawback for hardware realization. We present a low memory zerotree coder (LMZC), which requires much less working memory than SPIHT. The LMZC coding algorithm abandons the use of lists, defines a different tree structure, and merges the sorting pass and the refinement pass together. The main techniques of LMZC are the recursive programming and a top-bit scheme (TBS). In TBS, the top bits of transformed coefficients are used to store the coding status of coefficients instead of the lists used in SPIHT. In order to achieve high coding efficiency, shape-adaptive discrete wavelet transforms are used to transformation arbitrarily shaped objects. A compact emplacement of the transformed coefficients is also proposed to further reduce working memory. The LMZC carefully treats "don't care" nodes in the wavelet tree and does not use bits to code such nodes. Comparison of LMZC with SPIHT shows that for coding a 768 /spl times/ 512 color image, LMZC saves at least 5.3 MBytes of memory but only increases a little execution time and reduces minor peak signal-to noise ratio (PSNR) values, thereby making it highly promising for some memory limited applications.