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In this work, we study and analyze the contourlet transform for low bit-rate image coding. This image-based geometrical transform has been recently introduced to efficiently represent images with a spars set of coefficients. In order to explore the potentiality of this new transform as a tool for image coding, we developed a direct coding scheme that is based on using nonlinear approximation of images. We code the quantized transform coefficients as well as the significance map of an image in the contourlet transform domain. Based on the proposed approach, we analyzed the rate-distortion curves for a set of images and concluded that this coding approach, despite its redundancy, is visually competitive with a direct wavelet transform coder, and in particular, it is visually superior to wavelet coding for images with textures and oscillatory patterns.