Image coding based on a morphological representation of wavelet data

• Published in: IEEE transactions on image processing Vol. 8; no. 9; pp. 1161 - 1174
• Main Authors: Servetto, S.D., Ramchandran, K., Orchard, M.T.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.09.1999; Institute of Electrical and Electronics Engineers
• Subjects: Algorithm design and analysis; Algorithms; Applied sciences; Coders; Coding, codes; Decorrelation; Discrete cosine transforms; Discrete transforms; Exact sciences and technology; Image coding; Image processing; Information, signal and communications theory; Quantization; Representations; Shape; Signal and communications theory; Signal processing; State of the art; Statistics; Telecommunications and information theory; Wavelet; Wavelet coefficients; Wavelet domain; Experimental result; Image processing; Wavelet transformation; Coding; Mathematical morphology; Data compression
• ISSN: 1057-7149; 1941-0042
• DOI: 10.1109/83.784429

An experimental study of the statistical properties of wavelet coefficients of image data is presented, as well as the design of two different morphology-based image coding algorithms that make use of these statistics. A salient feature of the proposed methods is that, by a simple change of quantizers, the same basic algorithm yields high performance embedded or fixed rate coders. Another important feature is that the shape information of morphological sets used in this coder is encoded implicitly by the values of wavelet coefficients, thus avoiding the use of explicit and rate expensive shape descriptors, these proposed algorithms, while achieving nearly the same objective performance of state-of-the-art zerotree based methods, are able to produce reconstructions of a somewhat superior perceptual quality, due to a property of joint compression and noise reduction they exhibit.