An algorithm that integrates table indexing and quad-tree decomposition is proposed for cartoon image compression in this work. The proposed method includes 3 steps. First, colors in the color palette are selected based on the input image and a set of training images. Second, the input image is divided into blocks of size 16 by 16. The number of colors inside each block is checked. If the block has one uniform color or exactly two colors, no further processing is required. Otherwise, quad-tree decomposition will be performed for this block. The subdivision continues until all subblocks have either one or two colors. Then, the code for each subblock will be output in a depth-first order. If the subblock size reaches 2 x 2 and the number of colors in that block is still more than 2, no further subdivision is performed and a code that indicates colors of 4 pixels are output. Finally, to further reduce the size, the data part of the output stream is losslessly compressed by the LZW method. Experimental results are given to demonstrate the superior performance of the proposed method for cartoon image compression.
A multi-scale DCT-domain image registration technique for two MPEG video inputs is proposed in this work. Several edge detectors are first applied to the luminance component of DC coefficients to generate the so-called difference maps for each input image. Then, a threshold is selected for each difference map to filter out regions
of lower activity. Following that, we estimate the displacement parameters by examining the difference maps of the two input images associated with the same edge detector. Finally, the ultimate displacement vector is calculated by averaging the parameters from all detectors. In order to reach higher quality of the output mosaic,
1D alignment is locally applied to pixels around the boundaries of displacement that is decided in the previous step. It is shown that the proposed method reduces the computation complexity dramatically as compared to pixel-based image registration techniques while reaching a satisfactory result in composition. Moreover, we
discuss how the overlapping region affects the quality of alignment.
An image registration technique for compressed video such as motion JPEG or the I picture of MPEG based on the matching of DCT (Discrete Cosine Transform) coefficients is investigated in this research. Several simple features such as the DC value and a couple of low-frequency AC coefficients in the DCT domain are first extracted to indicate the edge strength and orientation inside each block for the image alignment purpose. Next, we conduct a coarse-level image segmentation task to filter out irrelevant regions. Then, for the regions of interest, we perform a more detail analysis to get the edge map. Finally, the alignment parameters are determined based on the information contained by the edge map. It is shown by experimental results that the proposed method reduces the computational cost of image registration dramatically as compared with the pixel domain registration technique while achieving certain quality of composition.
Several color matching algorithms are proposed to merge two or more video inputs of smaller sizes into one single video output of a larger size with a wider field of view for the video mosaic application. The main challenge is to remove apparent seam lines between image boundaries. All developed algorithms share the same basic idea with different implementation details. That is, color differences between input images are first compensated using either histogram equalization or polynomial-based contrast stretching techniques. Then, a linear filtering technique is adopted to remove seam lines between image boundaries. The algorithms are developed in both the pixel and the DCT domains. The compressed-domain processing is attractive since it reduces the computational complexity. It is shown by experimental results that the color matching problem can be solved satisfactorily even in the compressed domain.