IEEE Trans Image Process - Denoising-enhancing images on elastic manifolds.

Tópicos

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{ framework(1458) process(801) describ(734) }
{ imag(1057) registr(996) error(939) }
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Resumo

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.

Resumo Limpo

conflict demand simultan lowpass highpass process requir imag denois enhanc still present outstand challeng although great deal progress made mean adapt diffusiontyp algorithm advanc process method algorithm introduc famili secondord time partial differenti equat equat describ motion thin elast sheet damp environ also deriv variat approach context imag process new oper enabl better edg preserv denois applic offer adapt lowpass filter preserv highfrequ compon passband better adapt diffus filter offer slower error propag across edg explor action power oper context imag process exploit purpos wealth knowledg accumul physic mathemat action behavior oper result method general color andor textur imag process embed imag multidimension manifold specif applic propos new approach superresolut outlin

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