Denoising-enhancing images on elastic manifolds

The conflicting demands for simultaneous low-pass and high-pass processing, required in image denoising and enhancement, still present an outstanding challenge, although a great deal of progress has been made by means of adaptive diffusion-type algorithms. To further advance such processing methods and algorithms, we introduce a family of second-order (in time) partial differential equations. These equations describe the motion of a thin elastic sheet in a damping environment. They are also derived by a variational approach in the context of image processing. The new operator enables better edge preservation in denoising applications by offering an adaptive lowpass filter, which preserves high-frequency components in the pass-band better than the adaptive diffusion filter, while offering slower error propagation across edges. We explore the action of this powerful operator in the context of image processing and exploit for this purpose the wealth of knowledge accumulated in physics and mathematics about the action and behavior of this operator. The resulting methods are further generalized for color and/or texture image processing, by embedding images in multidimensional manifolds. A specific application of the proposed new approach to superresolution is outlined.