Statistics – Applications
Scientific paper
Oct 1997
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1997spie.3164..279s&link_type=abstract
Proc. SPIE Vol. 3164, p. 279-290, Applications of Digital Image Processing XX, Andrew G. Tescher; Ed.
Statistics
Applications
Scientific paper
This paper presents a new method for an efficient coding of image data. Based on the wavelet transform, the algorithm utilizes the remaining correlation between subbands. A successive approximation of wavelet coefficients yields a hierarchical symbol stream, which is highly compressed with a prediction of significant descendants. The coding algorithm distinguishes itself by a high adaptivity to the image content. The resulting bitstream contains all image information in order of its significance. Therefore it is possible to truncate the bitstream at any point, without endangering the decoding process. The advantages of such an embedded bitstream are spatial and rate-distortion scalability. Further improvement is obtained using anew adaptive wavelet transform known as wavelet packets. Contrary to earlier techniques, relevant statistical properties of the current subband are first analyzed. Dependent on that, the decomposition decision is made, whether the subband should be decomposed or not. This procedure yields not to a best-basis selection but to a near-optimal decomposition structure. The main advantage is the reduction of computational cost.
Mueller Erika
Schwartz Heiko
Strutz Tilo
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