In this paper, we study image description based on compound mutual
information (CMI) and its application to multimodal image registration. CMI is an aggregate information measure derived from
the multiple marginal densities of image distributions. It extends
histogram-based mutual information to that based on various marginal
densities, which encode spatial intensity distribution and other image characteristics. Therefore, CMI can overcome the difficulties (such as the lack of spatial information) inherent in the color histogram, enrich the vocabulary of image description, and help improve registration accuracy and robustness. CMI is not sensitive to
illumination and absolute appearance, and it is particularly suited for multimodal applications.
3D mesh modeling offers several advantages over 2D mesh modeling for object-based video manipulation including digital postprocessing and editing. This paper proposes a new method for automatic reconstruction of 3D affine and Euclidean mesh representations of objects from video sequences. Our approach is to first design a 2D mesh by selecting node points from a set of salient points followed by constrained Delaunay triangulation. Next, an improved 2D mesh tracking scheme is proposed that estimates motion vectors at the node points by global motion estimation followed by a local refinement scheme. A 3D mesh is then reconstructed by estimating the depth at these node points in an affine space using computer vision techniques. A Euclidean reconstruction is also computed by imposing additional constraints. Experimental results are provided to demonstrate the accuracy of the reconstructions.
We propose a joint source/channel coding scheme to transmit image through binary noisy channels based on 2-D discrete cosine transform (DCT) and trellis coded quantization (TCQ). When an image is transmitted through noisy channel with high throughput, both image compression and error-resilient coding scheme need to be considered. After the discrete cosine transform, the source image is decomposed into several subsources according to the transform coefficient positions, i.e., the same frequency coefficients in different DCT blocks are grouped together as a single subsource. The mean and variance values are used to construct the scalar codebooks for TCQ. Uniform threshold trellis coded quantizer is constructed to release the complexity and the transform coefficients are quantized by these fixed-rate quantizer and transmitted through noisy channels. No explicit error protection is used. The steepest descent method and iterative schemes are employed to determine the optimum bit allocation among the subsources subject to the constraints of the average coding rate and allowable maximum bits to each sample. Neighborhood relation is employed to limit the searching space when a bit is to be allocated to certain subsource. Simulation results show that the performance is very promising.
We propose in this paper a variable-coefficient fixed-length (VCFL) coding scheme for wavelet-based image transmission over noisy channels. When an image is transmitted through noisy channel with high throughput, both image compression and error-resistant coding scheme need to be considered. In this approach, an image is first decomposed into subbands by wavelet transform and quantized using an adaptive quantization scheme. The adaptive quantization is adaptive to both the frequency characteristics and the spatial constraints based on Gibbs random field. The traditional variable length entropy coding schemes, such as Huffman coding or arithmetic coding, and the fixed length coding such as LZW are usually very sensitive to channel noise for image transmission applications. Even with the insertion of synchronization symbols, they still cannot be directly employed without additional error correction/detection coding. To overcome the difficulty of image transmission over noisy channels, we propose to code the quantized subband coefficients with the VCFL scheme. This coding scheme attempts to keep the balance between redundancy removal, synchronization detection and error resilience. Part of the codebook is field based on the observation of the coefficient spatial distribution patterns in each subbands to alleviate the transmission of the codebook. The remaining code positions within the fixed length codebook can be utilized to combat channel errors by carefully arranging the code positions such that the codes with biggest transition cost will have the biggest Hamming distance. These positions can laos be filled with other frequently appeared coefficient composition sequences to achieve higher compression ratio. Experimental results of image transmission over noisy channels are reported to show the promising potential of the proposed coding scheme.
In wireless image communication, image compression is necessary because of the limited channel bandwidth. The associated channel fading, multipath distortion and various channel noises demand that the applicable image compression technique be amenable to noise combating and error correction techniques designed for wireless communication environment. In this study, we adopt a wavelet-based compression scheme for wireless image communication applications. The scheme includes a novel scene adaptive and signal adaptive quantization which results in coherent scene representation. Such representation can be integrated with the inherent layered structure of the wavelet-based approach to provide possibilities for robust protection of bit stream against impulsive and bursty error conditions frequently encountered in wireless communications. To implement the simulation of wireless image communication, we suggest a scheme of error sources modeling based on the analysis of the general characteristics of the wireless channels. This error source model is based on Markov chain process and is used to generate binary bit error patterns to simulate the bursty nature of the wireless channel errors. Once the compressed image bit stream is passed through the simulated channel, errors will occur according to this bit error pattern. Preliminary comparison between JPEG-based wireless image communication and wavelet-based wireless image communication has been made without application of error control and error resilience to either case. The assessment of the performance based on image quality evaluation shows that the wavelet-based approach is promising for wireless communication with the bursty channel characteristics.
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