The USC Andrew and Erna Viterbi School of Engineering USC Signal and Image Processing Institute USC Ming Hsieh Department of Electrical Engineering University of Southern California

Technical Report USC-SIPI-377

“Low Complexity Mosaicking and Up-Sampling Techniques for High Resolution Video Display”

by Ming-Sui Lee

December 2006

Several challenging issues for applications of image/video mosaicking and upsampling with high resolution are addressed here, all of which are mainly conducted in DCT (Discrete Cosine Transform) domain so that lower computation complexity can be achieved. First of all, color matching and compensation techniques are proposed to remove the seam lines between image boundaries due to the different color tones of the inputs. Color deviation of each input image is corrected first and color differences between input images are then compensated using the polynomial-based contrast stretching technique. The proposed approach is attractive for its lower computational complexity. Experimental results demonstrate that the color-matching problem can be satisfactorily solved in the compressed domain even when the DCT blocks of original input images are not aligned.Two block-level image registration techniques for compressed video such as motion JPEG or the I-picture of MPEG are investigated. The proposed methods are based on edge estimation and extraction in DCT domain so that the computational cost of image registration is reduced dramatically while achieving certain quality of composition. In order to reach higher accuracy of registration, hybrid block/pixel level alignment, is proposed so that the displacement vector resolution can be enhanced from the block level to the pixel level. The inverse DCT transform is not performed to the whole image but only to some selected blocks. It is shown by experiments that the proposed algorithm saves around 40% of the computational complexity while achieving the same quality.In the last part, a content adaptive technique is proposed to upsample an image to an output image of higher resolution. The proposed technique is a block-based processing algorithm that offers the flexibility in choosing the most suitable up-sampling method for a particular block type. For example, the unsharp masking method is applied to the textured region to preserve high frequency components and a more sophisticated technique, modified facet modeling followed by 1D unsharp masking, is adopted for processing edge blocks. Experimental results are given to demonstrate the efficiency of the proposed techniques.

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