. To provide a solid foundation for a good solution to this problem, "multiresolution decomposition and synthesis " approaches have been developed which decompose raw image data into a set of partial information channels, where each channel represents a certain modality (or aspect) of the raw image

We present a new technique for the display of high-dynamic-range images, which reduces the contrast while preserving detail. It is based on a two-scale decomposition of the image into a base layer, encoding large-scale variations, and a detail layer. Only the base layer has its contrast reduced

Abstract. In this paper, we study a type of reflected BSDE with a constraint and introduce a new kind of nonlinear expectation via BSDE with a constraint and prove the Doob-Meyer decomposition with respect to the super(sub)martingale introduced by this nonlinear expectation. We then apply

This paper presents a demosaicing approach via nonlinear image decomposition for a digital color camera. This approach is com-posed of four stages. At the first stage, with the multiplicative BV-G image-decomposition method, each primary color channel of ob-served raw color data mosaicked

We describe the Wavelet-Vaguelette Decomposition (WVD) of a linear inverse problem. It is a substitute for the singular value decomposition (SVD) of an inverse problem, and it exists for a class of special inverse problems of homogeneous type { such asnumerical di erentiation, inversion of Abel

Abstract. We prove global well-posedness for the defocusing cubic wave equation

The statistical properties of natural images suggest an optimal form of nonlinear decomposition, in which the image is decomposed using a set of linear filters at a variety of positions, scales and orientations, and these linear responses are then rectified and divided by a weighted sum

for design-space exploration of applications in this problem domain. We solve performance tuning as an optimization problem by formulating cost functions using results from queueing theory. This results in a mixed-integer nonlinear optimization problem which is NP-hard. We reduce the search complexity

sar target decomposition based on

derived using a conventionalproper orthogonaldecomposition. Although further development is necessary, the concept also extends to nonlinear systems. W Nomenclature h = airfoil plunge displacement K = proper orthogonal decomposition (POD) kernel m = number of POD snapshots n = number of states