Optimal Y-u-v Model Based on Karhunen-loeve Transformation
نویسنده
چکیده
An optimal Y-U-V transformation based on Karhunen-Loeve transformation for image compression proposed in this paper is considered as a spectral redundancy reduction. The PSNR is gained for optimal Y-U-V in comparison with traditional fixed Y-U-V transformation, because the variances are most separately after K-L transformation and the down sampling is taken on the coordinates with smallest variances in optimal Y-U-V transformation. The K-L transformation in optimal Y-U-V is an image-dependent transform that is to de-correlate the data in color spectral domain by using eigenvector matrix of covariance of the colors of the image. A normalization matrix follows the optimal Y-U-V transformation is used for ranging the data of Y-U-V within 0-255. The procedure is used in encoding only and the Y-U-V transformation can be transmitted with compressed data and de-coding easily.
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