Finite context models improve the performance of chain based encoders to the point that they become attractive, alternative models for binary image compression. The resulting code is within 4% of JBIG at 200 dpi and is 9% more e cient at 400 dpi.

Image coding requires an e ective representation of images to provide dimensionality reduction, a quantization strategy to maintain image quality, and nally the error free encoding of quantized coe cients. In the coding of quantized coe cients, Hu man coding and arithmetic coding have been used most commonly and are suggested as alternatives in the JPEG standard. In some recent w ork, zerotree coding has been proposed as an alternate method, that considers the dependence of of quantized coe cients from subband to subband, and thus appears as a generalization of the context-based approach often used with arithmetic coding. In this paper, we propose to review these approaches and discuss them as special cases of an analysis based approach to the coding of coe cients. The requirements on causality and computational complexity implied by arithmetic and zero-tree coding will be studied and other schemes proposed for the choice of the predictive coe cient c o n texts that are suggested by image analysis.

We compare several wavelet-based coders in the encoding of still images. Two image quality metrics are used in our comparative study: a perception-based, quantitative picture quality scale and the conventional distortion measure, peak signal-to-noise ratio. Coders are evaluated in the rate-distortion sense. The e ects of di erent wavelets, quantizers, and encoders are assessed individually. Two representative wavelets, three quantizers, three encoders, and the combinations of these components are compared. Our results provide insight into the design issues of optimizing wavelet coders, as well as a good reference for application developers to choose from an increasingly large family of wavelet coders for their applications.Subject terms: wavelets, wavelet transform, image coding and compression, image quality, distortion measure.

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Image coding is one of the most visible applications of wavelets. There has been increasing number of reports each y ear since the late 1980's on the design of new wavelet coders and variations to existing ones. In this paper, we report some results from our comparative study of wavelet image coders using a perception-based, quantitative picture quality scale as the distortion measure. Coders are evaluated in rate-distortion sense the in uences of di erent w avelets, quantizers, and encoders are assessed individually. Our results provide an insight i n to the design issues of optimizing wavelet coders, as well as a good reference for application developers to choose from an increasingly large family of wavelet coders for their applications.