27 November 2002 Fast algorithm of byte-to-byte wavelet transform for image compression applications
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Abstract
A new fast algorithm of 2D DWT transform is presented. The algorithm operates on byte represented images and performs image transformation with the Cohen-Daubechies-Feauveau wavelet of the second order. It uses the lifting scheme for the calculations. The proposed algorithm is based on the "checkerboard" computation scheme for non-separable 2D wavelet. The problem of data extension near the image borders is resolved computing 1D Haar wavelet in the vicinity of the borders. With the checkerboard splitting, at each level of decomposition only one detail image is produced that simplify the further analysis for data compression. The calculations are rather simple, without any floating point operation allowing the implementation of the designed algorithm in fixed point DSP processors for fast, near real time processing. The proposed algorithm does not possesses perfect restoration of the processed data because of rounding that is introduced at each level of decomposition/restoration to perform operations with byte represented data. The designed algorithm was tested on different images. The criterion to estimate quantitatively the quality of the restored images was the well known PSNR. For the visual quality estimation the error maps between original and restored images were calculated. The obtained simulation results show that the visual and quantitative quality of the restored images is degraded with number of decomposition level increasing but is sufficiently high even after 6 levels. The introduced distortion are concentrated in the vicinity of high spatial activity details and are absent in the homogeneous regions. The designed algorithm can be used for image lossy compression and in noise suppression applications.
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Oleksiy B. Pogrebnyak, Oleksiy B. Pogrebnyak, Juan Humberto Sossa Azuela, Juan Humberto Sossa Azuela, Pablo Manrique Ramirez, Pablo Manrique Ramirez, } "Fast algorithm of byte-to-byte wavelet transform for image compression applications", Proc. SPIE 4789, Algorithms and Systems for Optical Information Processing VI, (27 November 2002); doi: 10.1117/12.450878; https://doi.org/10.1117/12.450878
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