In block motion estimation, search patterns have a large impact on the searching speed and quality of performance. Based on motion vector distribution characteristics of real world video sequences, we propose a new cross-diamond search algorithm (NCDS) using cross-search patterns before large/small diamond search patterns in this paper. NCDS employs halfway technique to achieve significant speedup on sequence with (quasi-) stationary blocks. NCDS employs Modified Partial Distortion Criterion (MPDC), which results in fewer search points with similar distortion. Experimental results show that the improvements of NCDS over CDS can be up to a 16% gain on speedup while similar prediction accuracy is maintained, and NCDS provides faster searching speed and smaller distortions than other popular fast block-matching algorithms.

A novel object-based fractal monocular and stereo video compression scheme with quadtree- based motion and disparity compensation is proposed in this paper. Fractal coding is adopted and each object is encoded independently by a prior image segmentation alpha plane, which is defined exactly as in MPEG-4. The first n frames of right video sequence are encoded by using the circular prediction mapping (CPM) and the remaining frames are encoded by using the non contractive interframe mapping (NCIM). The CPM and NCIM methods accomplish the motion estimation/compensation of right video sequence. According to the different coding or user requirements, the spatial correlations between the left and right frames can be explored by partial or full affine transformation quadtree-based disparity estimation/compensation, or simply by applying CPM/NCIM on left video sequence.

A new object-based fractal stereo video coding scheme with quadtree-based disparity or motion compensation is proposed in this paper. Monocular or stereo video are compressed by using fractal coding and each object is encoded independently by a prior image segmentation alpha plane which is exactly the same as in MPEG-4. The first 2 frames of right video are encoded by using the Circular Prediction Mapping (CPM) and the remaining frames are encoded by using the Non Contractive Interframe Mapping (NCIM). The CPM and NCIM methods accomplish the motion estimation/compensation of right video (reference), and according to different coding or user requirements, the spatial correlations between left and right frames can be explored by partial or full affine transformation quadtree-based disparity estimation/compensation, or simply applying CPM/NCIM on left video. The experimental results indicate that we get high compression ratio and also good PSNR.

A novel object-based fractal stereo video coding scheme with quadtree-based disparity or motion compensation is proposed in this paper. Fractal coding is adopted and each object is encoded independently by a prior image segmentation alpha plane, which is defined exactly as in MPEG-4. The first 2 frames of right video are encoded by using the circular prediction mapping (CPM) and the remaining frames are encoded by using the non contractive interframe mapping (NCIM). The CPM and NCIM methods accomplish the motion estimation/compensation of right video. According to the different coding or user requirements, the spatial correlations between left and right frames can be explored by partial or full affine transformation quadtree-based disparity estimation/compensation, or simply applying CPM/NCIM on left video. The testing results for the nature stereo video sequences provide promising performances at low bitrate coding. We believe it will be a powerful and efficient technique for the object-based stereo video sequences coding.

Region-based functionality offered by the MPEG-4 video compression standard is also appealing for still images, for example to permit object-based queries of a still-image database. A popular method for still-image compression is fractal coding. However, traditional fractal image coding uses rectangular range and domain blocks. Although new schemes have been proposed that merge small blocks into irregular shapes, the merging process does not, in general, produce semantically-meaningful regions. We propose a new approach to fractal image coding that permits region-based functionalities; images are coded region by region according to a previously-computed segmentation map. We use rectangular range and domain blocks, but divide boundary blocks into segments belonging to different regions. Since this prevents the use of standard dissimilarity measure, we propose a new measure adapted to segment shape. We propose two approaches: one in the spatial and one in the transform domain. While providing additional functionality, the proposed methods perform similarly to other tested methods in terms of PSNR but often result in images that are subjectively better. Due to the limited domain-block codebook size, the new methods are faster than other fractal coding methods tested. The results are very encouraging and show the potential of this approach for various internet and still-image database applications.

The significant effort to provide region-based compression and functionality within the MPEG-4 standard is not paralleled in the still-image compression domain. In this paper, we propose an approach to fractal coding of still images that is truly region-based. Unlike previous fractal compression methods the proposed approach compresses an image region-by-region based on a prior segmentation, very much like in MPEG-4; individual regions can be decoded without full image decoding. The method performs the domain/range block matching in frequency domain using a shape-adaptive discrete cosine transform. Experimental results evaluating the performance of the approach are shown.

We propose a new image compression scheme based on fractal coding of wavelet transform coefficients using a fast non-iterative algorithm for the codebook generation. The original image is first decomposed into subbands containing information in different spatial directions and different scales, using an orthogonal wavelet filter bank. Subbands are encoded using local iterated function systems (LIFS) with range and domain blocks presenting horizontal or vertical directionalities. Their sizes are estimated according to the correlation lengths and resolution of each subband. The computational complexity is greatly decreased by using subband decomposition. In addition a fast non-iterative algorithm is implemented for block classification. This algorithm progressively creates the codebook during only one scanning of the training set. We prove the efficiency of the proposed approach both in terms of PSNR/bit rate and computation time.