Higher-order structure of natural images
نویسندگان
چکیده
We present a statistical model for learning efficient codes of higher-order structure in natural images. The model, a non-linear generalization of independent component analysis, replaces the standard assumption of independence for the joint distribution of coefficients with a distribution that is adapted to the variance structure of the coefficients of an efficient image basis. This offers a novel description of higher order image structure and provides a way to learn coarse-coded, sparse-distributed representations of abstract image properties such as object location, scale, and texture.
منابع مشابه
Learning higher-order structures in natural images.
The theoretical principles that underlie the representation and computation of higher-order structure in natural images are poorly understood. Recently, there has been considerable interest in using information theoretic techniques, such as independent component analysis, to derive representations for natural images that are optimal in the sense of coding efficiency. Although these approaches h...
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